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          Ecology and AI      Cache   Translate Page   Web Page Cache   
(Harvard University) Using more than three million photographs from the citizen science project Snapshot Serengeti, researchers trained a deep learning algorithm to automatically identify, count and describe animals in their natural habitats. Results showed the system was able to automate the process for up to 99.3 percent of images as accurately as human volunteers.
          Face clustering with Python      Cache   Translate Page   Web Page Cache   

Today’s blog post is inspired by a question from PyImageSearch reader, Leonard Bogdonoff. After I published my previous post on Face recognition with OpenCV and deep learning, Leonard wrote in and asked: Hey Adrian, can you go into identity clustering? I have a dataset of photos and I can’t seem to pinpoint how I would […]

The post Face clustering with Python appeared first on PyImageSearch.


          University Recruiter (Contract) - Intel - Hillsboro, OR      Cache   Translate Page   Web Page Cache   
Inside this Business Group. High level understanding of AI, Deep Learning, Machine Learning, etc. Regularly monitor candidate pipeline activity and share...
From Intel - Wed, 20 Jun 2018 10:37:58 GMT - View all Hillsboro, OR jobs
          Embedded ML Developer - Erwin Hymer Group North America - Virginia Beach, VA      Cache   Translate Page   Web Page Cache   
NVIDIA VisionWorks, OpenCV. Game Development, Accelerated Computing, Machine Learning/Deep Learning, Virtual Reality, Professional Visualization, Autonomous...
From Indeed - Fri, 22 Jun 2018 17:57:58 GMT - View all Virginia Beach, VA jobs
          Data Scientist - ZF - Northville, MI      Cache   Translate Page   Web Page Cache   
Deep Learning, NVIDIA, NLP). You will run cost-effective data dive-ins on complex high volume data from a variety of sources and develop data solutions in close...
From ZF - Thu, 21 Jun 2018 21:14:15 GMT - View all Northville, MI jobs
          Best of arXiv.org for AI, Machine Learning, and Deep Learning – June 2018 | insideBIGDATA      Cache   Translate Page   Web Page Cache   
In this recurring monthly feature, we filter recent research papers appearing on the arXiv.org preprint server for compelling subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the past month, as insideBIGDATA reports.
 

Researchers from all over the world contribute to this repository as a prelude to the peer review process for publication in traditional journals. arXiv contains a veritable treasure trove of learning methods you may use one day in the solution of data science problems. We hope to save you some time by picking out articles that represent the most promise for the typical data scientist. The articles listed below represent a fraction of all articles appearing on the preprint server. They are listed in no particular order with a link to each paper along with a brief overview. Especially relevant articles are marked with a “thumbs up” icon. Consider that these are academic research papers, typically geared toward graduate students, post docs, and seasoned professionals. They generally contain a high degree of mathematics so be prepared. 
Enjoy!
Read more...

Source: insideBIGDATA

          Deep Learning Expert (Software Engineer - Trimble Inc. - Toronto, ON      Cache   Translate Page   Web Page Cache   
Experience working on global projects with dispersed teams desired. Applanix, a Trimble company is seeking a Deep Learning Expert (Software Engineer) to fill an...
From Trimble Inc. - Tue, 10 Jul 2018 23:34:56 GMT - View all Toronto, ON jobs
          How Deep Learning Is Dispelling the Clouds Hanging Over Climate Models      Cache   Translate Page   Web Page Cache   

Global climate projections don’t always agree on how much the climate will warm in coming decades. Some project temperature rises of three or more degrees Celsius by the year 2100. Others predict a 1.5 degree shift. The primary reason for this variation may be surprising: clouds. “Most of the uncertainties we have — not all, Read article >

The post How Deep Learning Is Dispelling the Clouds Hanging Over Climate Models appeared first on The Official NVIDIA Blog.


          Nvidia AI can remove noise and artifacts from grainy photos      Cache   Translate Page   Web Page Cache   

Nvidia has developed an impressive deep learning technique capable of automatically removing noise and artifacts from photos. Whereas recent deep learning work in this field has focused on training a neural network with clean and noisy images, Nvidia’s AI can do so without ever being shown a noise-free example.

Read Entire ArticleRead Comments


          Embedded ML Developer - Erwin Hymer Group North America - Virginia Beach, VA      Cache   Translate Page   Web Page Cache   
NVIDIA VisionWorks, OpenCV. Game Development, Accelerated Computing, Machine Learning/Deep Learning, Virtual Reality, Professional Visualization, Autonomous...
From Indeed - Fri, 22 Jun 2018 17:57:58 GMT - View all Virginia Beach, VA jobs
          Data Scientist - ZF - Northville, MI      Cache   Translate Page   Web Page Cache   
Deep Learning, NVIDIA, NLP). You will run cost-effective data dive-ins on complex high volume data from a variety of sources and develop data solutions in close...
From ZF - Thu, 21 Jun 2018 21:14:15 GMT - View all Northville, MI jobs
          Spectral appoints Michael Walton as Vice President of Sales & Marketing to fuel Accelerated growth in demand for MemoryIP & software development tools for Design Automation      Cache   Translate Page   Web Page Cache   
...joined the company as Vice President of Sales and Marketing. With his extensive experience selling and marketing EDA tools and IP, Michael is well suited to drive sales growth and new market penetration at SDT. IOT business coupled with deep learning ...

          An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution      Cache   Translate Page   Web Page Cache   

As powerful and widespread as convolutional neural networks are in deep learning, AI Labs’ latest research reveals both an underappreciated failing and a simple fix.

The post An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution appeared first on Uber Engineering Blog.


          Revue de Presse Xebia      Cache   Translate Page   Web Page Cache   

La revue de presse hebdomadaire des technologies Big Data, DevOps et Web, architectures Java et mobilité dans des environnements agiles, proposée par Xebia. IoT Google lance un SDK pour Google Assistant  Front React Sketch.app Data Google met à jour Google Maps avec du Deep Learning DevOps Spotify partagent leur gestion des évènements Rancher annoncent Longhorn IoT...

L’article Revue de Presse Xebia est apparu en premier sur Blog Xebia - Expertise Technologique & Méthodes Agiles.


          One Stop Systems Showcases Composable Infrastructure for GPU Workloads at ISC 2018      Cache   Translate Page   Web Page Cache   

In this video from ISC 2018, Jaan Mannik from One Stop Systems describes the company's HPC systems and new composable infrastructure solutions. OneStop also showcased a wide array of its high-density NVIDIA GPU-based appliances, as well as showcase a live remote connection to one of its machine learning and HPC platforms. "OSS leads the market in external systems that increase a server's performance in HPC applications, reducing cost and impact on data center infrastructure. These technology-hungry applications include AI (artificial intelligence), deep learning, seismic exploration, financial modeling, media and entertainment, security and defense."

The post One Stop Systems Showcases Composable Infrastructure for GPU Workloads at ISC 2018 appeared first on insideHPC.


          Post-Doctoral Research Associate in Deep Learning for Intelligent Disease Monitoring in Lung …      Cache   Translate Page   Web Page Cache   
We are seeking a Research Associate to develop and test novel machine/deep learning based medical image analysis methods for our EPSRC ...
          (USA-CA-Oakland) Assistant Dean of Students (K-4)      Cache   Translate Page   Web Page Cache   
THE ORGANIZATION: Social justice movements come in all shapes and sizes. Here at Lighthouse Community Public Schools, we are engaged in an educational movement that goes beyond our classrooms working to disrupt educational inequities by providing our students and families exceptional educational opportunities every day. Grounded in our core values of community, integrity, agency, love, and social justice rooted in EL Education Model, LCPS is a leader in fostering innovative schools achieving exceptional student outcomes where each child is at the center of their own learning. Our mission is to prepare diverse students for college, a career of their choice, and to be lifelong changemakers. Founded in 2002, LCPS operates a high-achieving K-12 public charter school, and our K-8 sister site, Lodestar, that opened in Fall 2016; serving nearly 1,000 students in East Oakland. Lighthouse is a beacon for public education and our graduates fulfill the promise of a better, brighter Oakland. 95% of our graduates, almost all of whom are first-generation college students, are accepted into four-year colleges. We were named the Hart Vision Charter School of the Year in 2013, and the #1 high school for closing achievement for low-income Latino students in 2016. If the work we do here at LCPS appeals to your values regarding quality education for all then please join our movement! Learn more at www.lighthousecharter.org THE OPPORTUNITY: The Assistant Dean of Students at Lighthouse K-4- A Lighthouse Community Charter School- enthusiastically serves as a champion of student and school culture for our elementary school community. The Assistant Dean of Students is charged with creatively bringing our values of community, integrity, love, social justice, and agency to life resulting in a community where students are prepared for success in college and career of their choice. The Assistant Dean of Students primary responsibility lies in developing and supporting restorative practices and systems to ensure that all students are developing as upstanders within their community who are able to repair harm and find solutions to problems. The Assistant Dean of Students is central to creating and upholding a positive college going culture where all students belong and develop as lifelong learners and community changemakers. Primary Responsibilities The Assistant Dean of Students’ primary charge is to co-foster the school-wide conditions for our students to successfully build positive relationships and be accountable for their own behavior. To this end, the Assistant Dean of Students will: Collaboratively Build and Celebrate Positive College Going School Culture • Support the K-4 Dean of Students in implementing key whole-school activities to build and celebrate school culture, such as weekly community meetings, annual community-building trips, etc. • Support bridging and orientation activities for new students and families and Lighthouse teachers during the summer before the start of the school year. • Support development of opportunities for students to use their agency and voice to build culture and community in K-4. • Collaboratively identify ways to visually celebrate student achievement of character targets and living our values. Collaboratively Implement a Responsive and Restorative Behavior Management System • Using principles of Restorative Justice, collaborate with the Dean of Students, Principal and RTI Director to implement a responsive behavior system that clearly articulates the school-wide systems and supports students will use to build positive relationships and manage their own behavior. • Facilitate Restorative Justice experiences between community members. Restoratively Manage Behavior Support Systems including Student Referrals & Interventions • Support the implementation of school wide consistent practices to support students’ positive inclusion in all learning spaces. • In collaboration with the K-4 Dean of Students, respond to student referrals with a restorative and responsive lens as well as appropriate behavior modification strategies. • Collect, input, and monitor effectiveness of individual student behavior referrals using our student data system. Family Communication & Support • Support and facilitate learning experiences for Lighthouse families, including facilitating evening family meetings as needed.. • Provide targeted pre-emptive support for families of students with needs based on assigned case-load (e.g. previously retained, acute stress or trauma, identified COST students). • Clearly and consistently communicate with all stakeholders, especially families, about student referrals and progress of interventions. Other duties as assigned by supervisor Core Competencies We are looking for educators who exhibit competencies in our 5 tenets: High Expectations for All • Asset-Based & Equity-Focused Urban Educator: Believes and demonstrates that every student can learn and commits to holding high expectations and an assets-based mindset even when students make mistakes. • Models Growth Mindset: Holds a growth-mindset for self, colleagues, and students demonstrated by self-reflection and the belief that everyone is a lifelong learner. Deep Learning • Restorative Learning: Supports students to have agency to find solutions to mistakes and fix harm. Harm and mistakes done to the community are seen as learning opportunities to repair relationships for the good of all involved and the community. • Data Analyst: Transparently uses and analyzes student data to support students and identify school-wide patterns. Serving the Whole Person & Engaging Families • Community Builder: Ensures a safe learning community that promotes a sense of belonging by building deep relationships, using restorative and responsive practices, addressing the whole person, embracing diversity and communicating effectively with students, families, colleagues, and community. Professional Learning Community • Skilled Collaborator: Collaborates with empathy by listening to divergent perspectives and demonstrating mission-alignment, knowledge of child development and socio-emotional learning, and high levels of professionalism at all times. • Strategic Teammate: Works in a strategic manner autonomously and collaboratively despite complexity. Minimum Qualifications • AA or equivalent required, B.A. preferred • 2+ years of experience working in schools or youth development programs, required • Spanish language proficiency preferred Supervision This position reports to the K-4 Dean of Students. TIME COMMITMENT This position is an 11-month non-exempt salaried position. The K-4 Assistant Dean of Students is expected to maintain hours of 8:00am - 4:00 pm M/T/Th/F and 8:00-5:00pm on W, including a ½ hour, duty-free lunch break, as well as attend occasional evening and weekend events outside of regular working hours. COMPENSATION Commensurate with experience. Competitive benefits package. TO APPLY People of color and bilingual candidates are strongly encouraged to apply. Interested candidates should submit: • Resume • Cover letter describing your interest in this exciting position and why you are an optimal fit, including how your educational philosophy, approach to student learning and behavior, and expertise would contribute to the Lighthouse team • 3 references with Name, Email, Phone Number and Title/nature of working relationship Application submission screening and initial phone interviews will be completed on a rolling basis until filled. In-person interviews and performance tasks will take place on-site. Lighthouse Community Charter Public Schools is an equal opportunity employer committed to diversity at all levels.
          Embedded ML Developer - Erwin Hymer Group North America - Virginia Beach, VA      Cache   Translate Page   Web Page Cache   
NVIDIA VisionWorks, OpenCV. Game Development, Accelerated Computing, Machine Learning/Deep Learning, Virtual Reality, Professional Visualization, Autonomous...
From Indeed - Fri, 22 Jun 2018 17:57:58 GMT - View all Virginia Beach, VA jobs
          Data Scientist - ZF - Northville, MI      Cache   Translate Page   Web Page Cache   
Deep Learning, NVIDIA, NLP). You will run cost-effective data dive-ins on complex high volume data from a variety of sources and develop data solutions in close...
From ZF - Thu, 21 Jun 2018 21:14:15 GMT - View all Northville, MI jobs
          Ecology and AI      Cache   Translate Page   Web Page Cache   
(Harvard University) Using more than three million photographs from the citizen science project Snapshot Serengeti, researchers trained a deep learning algorithm to automatically identify, count and describe animals in their natural habitats. Results showed the system was able to automate the process for up to 99.3 percent of images as accurately as human volunteers. (Source: EurekAlert! - Biology)
          Online dating is using big data to find compatible matches      Cache   Translate Page   Web Page Cache   
Deep learning analyzes images of people's faces to identify specific features. Key characteristics can be recognized to differentiate between different ...
          Online dating is using big data to find compatible matches      Cache   Translate Page   Web Page Cache   
Deep learning analyzes images of people's faces to identify specific features. Key characteristics can be recognized to differentiate between different ...
          How Quantum Computing Will Change The Face Of Artificial Intelligence      Cache   Translate Page   Web Page Cache   
Will quantum computing change deep learning? Given how leading tech giants like IBM and Google, among others, are racing to make it a reality, ...
          How Quantum Computing Will Change The Face Of Artificial Intelligence      Cache   Translate Page   Web Page Cache   
Will quantum computing change deep learning? Given how leading tech giants like IBM and Google, among others, are racing to make it a reality, ...
          Drones survey African wildlife      Cache   Translate Page   Web Page Cache   
To decipher this mass of raw visual data, the researchers used a kind of artificial intelligence (AI) known as "deep learning". Conceived by PhD ...
          Drones survey African wildlife      Cache   Translate Page   Web Page Cache   
To decipher this mass of raw visual data, the researchers used a kind of artificial intelligence (AI) known as "deep learning". Conceived by PhD ...
          Nvidia and MIT get a step closer to ‘Computer, enhance’ image cleaning      Cache   Translate Page   Web Page Cache   
As data gets bigger and models grow larger, deep learning is once again "completely gated by hardware." At the VLSI Symposia, Nvidia suggested ...
          Nvidia and MIT get a step closer to ‘Computer, enhance’ image cleaning      Cache   Translate Page   Web Page Cache   
As data gets bigger and models grow larger, deep learning is once again "completely gated by hardware." At the VLSI Symposia, Nvidia suggested ...
          Post-Doctoral Research Associate in Deep Learning for Intelligent Disease Monitoring in Lung …      Cache   Translate Page   Web Page Cache   
We are seeking a Research Associate to develop and test novel machine/deep learning based medical image analysis methods for our EPSRC ...
          Samsung Foundry certifica le soluzioni di Ansys      Cache   Translate Page   Web Page Cache   

I clienti di Samsung Foundry e Ansys potranno creare una nuova generazione di dispositivi elettronici solidi e affidabili grazie alla certificazione di Samsung Foundry e all’abilitazione delle soluzioni Ansys per l’analisi della power integrity e dell’affidabilità. Questa certificazione permette l’estrazione, l’analisi statica e dinamica delle cadute di tensione, l’analisi dei fenomeni di self-heating ed elettromigrazione per reti sia elettriche sia di segnale per la recentissima tecnologia di processo litografica 7LPP (7-nanometer Low Power Plus) di Samsung Foundry.

“Con la tecnologia 7LPP i clienti hanno la possibilità di creare prodotti innovativi per una connettività seamless con il 5G e i dispositivi smart basati sull’intelligenza artificiale per le applicazioni automotive, mobile e HPC di nuova generazione”, dichiara Ryan Sanghyun Lee, vice president del Foundry Marketing Team di Samsung Electronics. “Grazie alle soluzioni Ansys certificate per 7LPP, i nostri clienti possono creare chipset mobile 5G ottimizzati dal punto di vista del consumo energetico e di dimensioni più contenute per essere utilizzati in telefoni ancora più sottili e costruire chip IA per applicazioni di deep learning ad alta intensità di calcolo per cloud ed edge computing”.

L'articolo Samsung Foundry certifica le soluzioni di Ansys è un contenuto originale di Elettronica News.


          LabView 2018 di NI promette migliori prestazioni di test      Cache   Translate Page   Web Page Cache   

NI ha rilasciato LabVIEW 2018. Le nuove funzioni permettono di rafforzare l’affidabilità del codice automatizzando lo sviluppo e l’esecuzione del software attraverso l’integrazione con strumenti di interfaccia aperti. Per i team di test che utilizzano FPGA per l’elaborazione, nuove funzioni di deep learning e operazioni in virgola mobile ottimizzate permettono di accorciare notevolmente il time to market.

“L’impegno costante di NI nello sviluppo di piattaforme software-centriche ci permette di sviluppare più rapidamente, ottenendo un ROI più elevato”, ha spiegato Chris Cilino, LabVIEW Framework Architect – Cirrus LogicLabVIEW. “LabVIEW ci permette di ridurre al minino i task per aggiungere test o modifiche al codice al nostro framework di validazione, offrendo un processo costante per mantenere il nostro software e integrare il riutilizzo di codice”. 

L'articolo LabView 2018 di NI promette migliori prestazioni di test è un contenuto originale di Elettronica News.


          #ICML2018 Tutorial: Toward theoretical understanding of deep learning, Sanjeev Arora       Cache   Translate Page   Web Page Cache   
Sanjeev is giving a tutorial at ICML entitled Toward theoretical understanding of deep learning. the presentation and all the references are all on this page. (and yes compressive sensing shows up in different parts)














Join the CompressiveSensing subreddit or the Google+ Community or the Facebook page and post there !
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          University Recruiter (Contract) - Intel - Hillsboro, OR      Cache   Translate Page   Web Page Cache   
Inside this Business Group. High level understanding of AI, Deep Learning, Machine Learning, etc. Regularly monitor candidate pipeline activity and share...
From Intel - Wed, 20 Jun 2018 10:37:58 GMT - View all Hillsboro, OR jobs
          The Best Tools for Lazy (but Successful) Developers      Cache   Translate Page   Web Page Cache   
Person sitting on a couch with a laptop

Laziness is a desirable trait for software developers, and they admit so themselves. For example, Philipp Lenssen, a well-known German-born developer who ran a successful blog Google Blogoscoped, once wrote:

"Only lazy programmers will want to write the kind of tools that might replace them in the end. Only a lazy programmer will avoid monotonous, repetitive code. The tools and processes inspired by laziness speed up production."

In addition to developing tools that help others, each successful developer also has a special kit of must-have tools that allow them to enjoy a little laziness by taking on some of their responsibilities.

In this article, we’re going to review the best tools that you can also add to your own kit.

1. Rescue Time: For Effective Time Management

If you’re not taking advantage of time management apps, you’re definitely missing some great opportunities to improve your daily schedule and free more time for doing other things than work.

Rescue Time is a great option to use. This time management app gives you a clear picture of how you’re using your computer throughout the day, thus helping you to understand your daily habits.

To help you improve your daily routine, the app generates a daily report to show you what things are stealing your precious time. Most users of Rescue Time say they are shocked to discover how much time they waste every day that they could potentially use for something better.

2. LocalStack: For Online Developing and Testing Cloud Apps

The next item on our list is a great local AWS cloud stack that provides an easy-to-use and test framework for developing cloud applications. LocalStack creates a testing environment on your local computer while allowing to maintain the functionality of the real AWS cloud environment.

The free version of LocalStack has core AWS services, community updates, bug fixes, and other helpful functions so you can enjoy cost-effective testing on your local machine for no cost.

3. Topol.io: For Creating Responsive Emails

Email marketing continues to be a big source of revenues for online businesses in 2018, so more and more companies are looking for developers to design responsive emails for their campaigns.

That’s where Topol.io comes in. A visual, drag-and-drop HTML editor for creating such emails has a wide variety of elements to attract the attention of receivers and entice them to click on CTA buttons.

The tool was developed by professional marketers and web designers and provides a number of templates for you to work with (you can also start from scratch). The editor has an intuitive environment, so you’ll be creating beautiful emails in no time.

4. Kur: Descriptive Deep Learning

This is an internal deep learning tool designed for developers looking to get their ideas off the ground more easily. According to the developers of Kur, it allows to design, train, and evaluate deep learning models without ever needing to code, which is something that can accelerate the process of building and training deep learning models.

Collaboration on models and shared learning is also possible with the tool, so anyone interested in getting more knowledge of deep learning can share their models and work with others.

Scott Stephenson, CEO of Deepgram, the company that developed Kur, had this to say about the usefulness of the tool: "You can start with classifying images and end up with self-driving cars. The point is giving someone that first little piece and then people can change the model and make it do something different."

5. UnDraw: Collection of SVG Images

If you’re looking for a great alternative to stock images, you just found one. unDraw is essentially a large online collection of beautiful images that any developer can use free and without attribution to create apps, websites, and other products.

Each of the images has an editable code so you can animate with plain css and change colors to make sure that the image fits your project. Also, you’ll enjoy the fact that you can scale the images on UnDraw without quality change, add own colors, embed codes directly into your html, and use on-the-fly generator to customize main color.

6. Google Fonts: For Beautiful Fonts

This is one of the most valuable resources in terms of web typography. The quality of font selection is unbelievable and you can use them for personal purposes such as formatting a professional essay and commercial purposes such as website fonts.

Since the use of typography as an essential design element is a huge trend in web development now, Google Fonts will be a highly useful tool. Moreover, all fonts are optimized for interfaces, reading on mobile devices, and UI-optimized.

Here are some examples of a beautiful use of Google Fonts from WebpageFX for your inspiration.

7. Castor: For Data Presentation

A useful tool for developers who need to present data on various screens. It provides the tools one needs to present data in a professional and attractive way on any screen, from a tablet to a wall-mounted TV.

Drag-and-drop tools, premade widgets, and many other features allow to edit data easily and quickly.

8. Slack: For Team Programming Assignments

This tool is one the most advanced team collaboration hubs for programmers out there. Organized conversations, searchable history, channel for collaboration, file sharing, voice and video calls, drag-and-drop images, videos, PDFs and other files, feedback, and easy threat management – all of this is possible with Slack.

Programmers who use Slack for team projects also love that it allows integration with Dropbox, Google Drive, SalesForce, and many other apps they use in their work (over 1,000 apps can be connected).

9. Passbolt: for Effective Password Management

According to Q4 2017 Website Security Insider analysis from SiteLock, an average website is attacked 44 times a day, and about 1 percent of all websites out there is hacked every week. A major reason of why a large share of these websites are hacked is a weak (or even not-so-weak password).

Passbolt is a free, open source, self-hosted password manager that protects passwords using the latest technology and is specifically built for teams of developers.

10. Visual Studio Code: for Cross Platform Code Editing

The last item on our list is a go-to code editor of choice for thousands of web developers around the world. The reason why they chose Visual Studio Code is its extensibility, customizability, integrated Git Control, IntelliSense, and many other helpful features, all for free!

Conclusion

As you can see, lazy doesn't have to mean unproductive. Most developers are work-aholics so they don't have to work.

Do you have an tip or trick to make your life easier as a developer? Which tool makes you lazy? Post your comments below and let's discuss.


          Innovation in healthcare: A hacker’s dream and CISO’s nightmare?      Cache   Translate Page   Web Page Cache   
For example, researchers at Stanford University last year announced that they had successfully trained a deep learning algorithm to identify skin ...
          Alphabet’s Verily takes its disease-fighting automated sex sorter for mosquitoes to Queensland      Cache   Translate Page   Web Page Cache   
Google's deep learning algorithm could more accurately detect a patient's risk of heart disease and stroke using a scan of their retina.
          (USA-CA-Santa Clara) Embedded Software Engineer      Cache   Translate Page   Web Page Cache   
Embedded Software Engineer (Computer Vision) Embedded Software Engineer (Computer Vision) - Skills Required - C, Embedded Software, Computer Vision, Linux, Video Processing, Deep Learning If you are an Embedded Software Engineer with Video Processing,Computer Vision, or Deep Learning experience please read on! **Top Reasons to Work with Us** 1. Based in Santa Clara, we are a leading developer of low-power, high-definition and Ultra HD video compression and image processing solutions. 2. Our company has been around for over a decade, so we offer a unique balance of stability and a small, tight-knit feel. 3. You will have the chance to work on exciting new development projects with a talented team. **What You Will Be Doing** - Design, implement, and test system software, including low level firmware, RTOS and embedded Linux kernel and applications. - Board bring up and testing. - Measure the performance of the microcode system and identify ways to improve it on a multi-thread/multi-core platform. - Create test and debugging tools for both internal and external customers. - Interact with key customers to understand requirements, develop new features, and assist in debug and getting to market. - Map requirements and algorithms to DSP and system software - Develop tools to aid software development. **What You Need for this Position** - Bachelors and or Masters degree in EE, CS, or Mathematics or equivalent. - 3 to 8 years hands-on experience software development. - Experience with Linux in embedded systems. - In-depth knowledge of C. - Experience with video processing, computer vision, or deep learning - Well versed in software engineering processes and understand how to develop and debug firmware for custom ASICs. - Experience with automotive software a plus. **What's In It for You** - Competitive salary - Full Benefits - 401k - PTO - Great Place to Work So, if you are an Embedded Software Engineer with Video Processing,Computer Vision, or Deep Learning experience, please apply today! Applicants must be authorized to work in the U.S. **CyberCoders, Inc is proud to be an Equal Opportunity Employer** All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, or any other characteristic protected by law. **Your Right to Work** – In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire. *Embedded Software Engineer* *CA-Santa Clara* *PG2-1467039*
          (USA-CA-San Carlos) Software Architect - Java/Android      Cache   Translate Page   Web Page Cache   
Software Architect - Java/Android Software Architect - Java/Android - Skills Required - Java, Android SDK, JavaScript, Android Framework, OpenGL, UI/UX, Connected Products OR Camera based app, Mandarin (Nice to have) Based in Redwood City, we offer devices featuring advanced AI and deep learning that enhances the quality of life by delivering information and performing tasks through audio and visual interactions. Currently, we are looking to bring on a Software Architect who has strong Java and Android SDK experience. If you would like to design the framework of our software and lead a team of software engineers to develop front-end and back-end software of our global products, we would love the time to tell you more about this amazing opportunity! - Will provide a transfer of sponsorship if need be. **Top Reasons to Work with Us** 1. Global company in earlier stages with startup vibe 2. Opportunity to make a huge impact - Your voice will be heard! 3. Work with a world-class scientific advisory committee and alongside very bright scientists, engineers, and business leaders 4. 2016/2017 Award winning products! **What You Will Be Doing** - Design the framework of our software and lead a team of software engineers to develop front-end and back-end software of our products. - Work closely with product and design team to push our product to the next stage. - Design software framework - Work with product team to plan product roadmap - Design and develop SDK for products - Build and implement new features - Identify and resolve Android application issues - Work closely with product and design to continually improve the user experience **What You Need for this Position** - Must have a CS degree (or related fields) - 8+ years of professional software development experience - 5+ years of Android application development experience (Android SDK and Java) - Played a leading role in shipping 2+ products from start to finish - UI/UX experience - Making things pretty for consumers. - Proficient with JavaScript -Nice to have/Preferred skills: - MS in CS - Deep understanding of Android Framework - Experience with OpenGL - Experience with back-end deployment and cloud based service - Experience developing AR/VR apps, social apps, and/or wearable hardware device as an engineer - Experience engaging and influencing senior executives **What's In It for You** 1. Competitive Salary 2. Bonus 3. PTO 4. 401K 5. Benefits So, if you are a Software Architect ready to make the career leap of your lifetime, please apply now! Applicants must be authorized to work in the U.S. **CyberCoders, Inc is proud to be an Equal Opportunity Employer** All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, or any other characteristic protected by law. **Your Right to Work** – In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire. *Software Architect - Java/Android* *CA-San Carlos* *AY2-1466993*
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           Nvidia's new AI takes a one-stop approach to fixing grainy photos       Cache   Translate Page   Web Page Cache   

The Noise2Noise AI image-enhancing technology was developed by researchers from NVIDIA, MIT and Finland’s Aalto University#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

If you've ever taken a photo in low light you've probably encountered the grainy effect that can dilute the finished product. A new AI tool could prove an incredibly easy way to remove this so-called noise, with the ability to automatically produce a clean image after analyzing only the corrupted version.

.. Continue Reading Nvidia's new AI takes a one-stop approach to fixing grainy photos

Category: Digital Cameras

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          Adaptive Adversarial Attack on Scene Text Recognition. (arXiv:1807.03326v1 [cs.CV])      Cache   Translate Page   Web Page Cache   

Authors: Xiaoyong Yuan, Pan He, Xiaolin Andy Li

Recent studies have shown that state-of-the-art deep learning models are vulnerable to the inputs with small perturbations (adversarial examples). We observe two critical obstacles in adversarial examples: (i) Strong adversarial attacks require manually tuning hyper-parameters, which take longer time to construct a single adversarial example, making it impractical to attack real-time systems; (ii) Most of the studies focus on non-sequential tasks, such as image classification and object detection. Only a few consider sequential tasks. Despite extensive research studies, the cause of adversarial examples remains an open problem, especially on sequential tasks. We propose an adaptive adversarial attack, called AdaptiveAttack, to speed up the process of generating adversarial examples. To validate its effectiveness, we leverage the scene text detection task as a case study of sequential adversarial examples. We further visualize the generated adversarial examples to analyze the cause of sequential adversarial examples. AdaptiveAttack achieved over 99.9\% success rate with 3-6 times speedup compared to state-of-the-art adversarial attacks.


          Complex Fully Convolutional Neural Networks for MR Image Reconstruction. (arXiv:1807.03343v1 [cs.CV])      Cache   Translate Page   Web Page Cache   

Authors: Muneer Ahmad Dedmari, Sailesh Conjeti, Santiago Estrada, Phillip Ehses, Tony Stöcker, Martin Reuter

Undersampling the k-space data is widely adopted for acceleration of Magnetic Resonance Imaging (MRI). Current deep learning based approaches for supervised learning of MRI image reconstruction employ real-valued operations and representations by treating complex valued k-space/spatial-space as real values. In this paper, we propose complex dense fully convolutional neural network ($\mathbb{C}$DFNet) for learning to de-alias the reconstruction artifacts within undersampled MRI images. We fashioned a densely-connected fully convolutional block tailored for complex-valued inputs by introducing dedicated layers such as complex convolution, batch normalization, non-linearities etc. $\mathbb{C}$DFNet leverages the inherently complex-valued nature of input k-space and learns richer representations. We demonstrate improved perceptual quality and recovery of anatomical structures through $\mathbb{C}$DFNet in contrast to its real-valued counterparts.


          What is Deep Learning | Deep Learning and its Applications | Deep Learning Tutorial Video - ExcelR      Cache   Translate Page   Web Page Cache   
ExcelR : Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Things you will learn in this video 1)What is deep learning? 2)Deep learning and its applications 3)Which algorithm behind deep learning? 4)How Neural network will work? To buy eLearning course on Data Science click here https://goo.gl/oMiQMw To register for classroom training click here https://goo.gl/UyU2ve To Enroll for virtual online training click here " https://goo.gl/JTkWXo" SUBSCRIBE HERE for more updates: https://goo.gl/WKNNPx For Introduction to Deep Learning Tutorial click here Deep Learning Tutorial For Beginners For Artificial Neural Network Tutorial click here https://goo.gl/a5tAjn #ExcelRSolutions #DeepLearning #Applicationsofdeeplearning #NeuralNetwork #R-programming #DataScienceCertification #DataSciencetutorial #DataScienceforbeginners #DataScienceTraining ----- For More Information: Toll Free (IND) : 1800 212 2120 | +91 80080 09706 Malaysia: 60 11 3799 1378 USA: 001-844-392-3571 UK: 0044 203 514 6638 AUS: 006 128 520-3240 Email: enquiry@excelr.com Web: www.excelr.com Connect with us: Facebook: https://www.facebook.com/ExcelR/ LinkedIn: https://www.linkedin.com/company/exce... Twitter: https://twitter.com/ExcelrS G+: https://plus.google.com/+ExcelRSolutions
          Who is Killed by Police: Introducing Supervised Attention for Hierarchical LSTMs. (arXiv:1807.03409v1 [cs.CL])      Cache   Translate Page   Web Page Cache   

Authors: Minh Nguyen, Thien Huu Nguyen

Finding names of people killed by police has become increasingly important as police shootings get more and more public attention (police killing detection). Unfortunately, there has been not much work in the literature addressing this problem. The early work in this field \cite{keith2017identifying} proposed a distant supervision framework based on Expectation Maximization (EM) to deal with the multiple appearances of the names in documents. However, such EM-based framework cannot take full advantages of deep learning models, necessitating the use of hand-designed features to improve the detection performance. In this work, we present a novel deep learning method to solve the problem of police killing recognition. The proposed method relies on hierarchical LSTMs to model the multiple sentences that contain the person names of interests, and introduce supervised attention mechanisms based on semantical word lists and dependency trees to upweight the important contextual words. Our experiments demonstrate the benefits of the proposed model and yield the state-of-the-art performance for police killing detection.


          Developing Brain Atlas through Deep Learning. (arXiv:1807.03440v1 [cs.CV])      Cache   Translate Page   Web Page Cache   

Authors: Asim Iqbal, Romesa Khan, Theofanis Karayannis

To uncover the organizational principles governing the human brain, neuroscientists are in need of developing high-throughput methods that can explore the structure and function of distinct brain regions using animal models. The first step towards this goal is to accurately register the regions of interest in a mouse brain, against a standard reference atlas, with minimum human supervision. The second step is to scale this approach to different animal ages, so as to also allow insights into normal and pathological brain development and aging. We introduce here a fully automated convolutional neural network-based method (SeBRe) for registration through Segmenting Brain Regions of interest in mice at different ages. We demonstrate the validity of our method on different mouse brain post-natal (P) developmental time points, across a range of neuronal markers. Our method outperforms the existing brain registration methods, and provides the minimum mean squared error (MSE) score on a mouse brain dataset. We propose that our deep learning-based registration method can (i) accelerate brain-wide exploration of region-specific changes in brain development and (ii) replace the existing complex brain registration methodology, by simply segmenting brain regions of interest for high-throughput brain-wide analysis.


          Predicting property damage from tornadoes with deep learning. (arXiv:1807.03456v1 [stat.ML])      Cache   Translate Page   Web Page Cache   

Authors: Jeremy Diaz, Maxwell Joseph

Tornadoes are the most violent of all atmospheric storms. In a typical year, the United States experiences hundreds of tornadoes with associated damages on the order of one billion dollars. Community preparation and resilience would benefit from accurate predictions of these economic losses, particularly as populations in tornado-prone areas continue to increase in density and extent. Here, we use artificial neural networks to predict tornado-induced property damage using publicly available data. We find that the large number of tornadoes which cause zero property damage (30.6% of the data) poses a challenge for predictive models. We developed a model that predicts whether a tornado will cause property damage to a high degree of accuracy (out of sample accuracy = 0.829 and AUROC = 0.873). Conditional on a tornado causing damage, another model predicts the amount of damage. When combined, these two models yield an expected value for the amount of property damage caused by a tornado event. From the best-performing models (out of sample mean squared error = 0.089 and R2 = 0.473), we provide an interactive, gridded map of monthly expected values for the year 2018. One major weakness is that the model predictive power is optimized with log-transformed, mean-normalized property damages, however this leads to large natural-scale residuals for the most destructive tornadoes. The predictive capacity of this model along with an interactive interface may provide an opportunity for science-informed tornado disaster planning.


          SceneEDNet: A Deep Learning Approach for Scene Flow Estimation. (arXiv:1807.03464v1 [cs.CV])      Cache   Translate Page   Web Page Cache   

Authors: Ravi Kumar Thakur, Snehasis Mukherjee

Estimating scene flow in RGB-D videos is attracting much interest of the computer vision researchers, due to its potential applications in robotics. The state-of-the-art techniques for scene flow estimation, typically rely on the knowledge of scene structure of the frame and the correspondence between frames. However, with the increasing amount of RGB-D data captured from sophisticated sensors like Microsoft Kinect, and the recent advances in the area of sophisticated deep learning techniques, introduction of an efficient deep learning technique for scene flow estimation, is becoming important. This paper introduces a first effort to apply a deep learning method for direct estimation of scene flow by presenting a fully convolutional neural network with an encoder-decoder (ED) architecture. The proposed network SceneEDNet involves estimation of three dimensional motion vectors of all the scene points from sequence of stereo images. The training for direct estimation of scene flow is done using consecutive pairs of stereo images and corresponding scene flow ground truth. The proposed architecture is applied on a huge dataset and provides meaningful results.


          An Adaptive Learning Method of Restricted Boltzmann Machine by Neuron Generation and Annihilation Algorithm. (arXiv:1807.03478v1 [cs.NE])      Cache   Translate Page   Web Page Cache   

Authors: Shin Kamada, Takumi Ichimura

Restricted Boltzmann Machine (RBM) is a generative stochastic energy-based model of artificial neural network for unsupervised learning. Recently, RBM is well known to be a pre-training method of Deep Learning. In addition to visible and hidden neurons, the structure of RBM has a number of parameters such as the weights between neurons and the coefficients for them. Therefore, we may meet some difficulties to determine an optimal network structure to analyze big data. In order to evade the problem, we investigated the variance of parameters to find an optimal structure during learning. For the reason, we should check the variance of parameters to cause the fluctuation for energy function in RBM model. In this paper, we propose the adaptive learning method of RBM that can discover an optimal number of hidden neurons according to the training situation by applying the neuron generation and annihilation algorithm. In this method, a new hidden neuron is generated if the energy function is not still converged and the variance of the parameters is large. Moreover, the inactivated hidden neuron will be annihilated if the neuron does not affect the learning situation. The experimental results for some benchmark data sets were discussed in this paper.


          DLOPT: Deep Learning Optimization Library. (arXiv:1807.03523v1 [cs.LG])      Cache   Translate Page   Web Page Cache   

Authors: Andrés Camero, Jamal Toutouh, Enrique Alba

Deep learning hyper-parameter optimization is a tough task. Finding an appropriate network configuration is a key to success, however most of the times this labor is roughly done. In this work we introduce a novel library to tackle this problem, the Deep Learning Optimization Library: DLOPT. We briefly describe its architecture and present a set of use examples. This is an open source project developed under the GNU GPL v3 license and it is freely available at https://github.com/acamero/dlopt


          Window Opening Model using Deep Learning Methods. (arXiv:1807.03610v1 [cs.LG])      Cache   Translate Page   Web Page Cache   

Authors: Romana Markovic, Eva Grintal, Daniel Wölki, Jérôme Frisch, Christoph van Treeck

Occupant behavior (OB) and in particular window openings need to be considered in building performance simulation (BPS), in order to realistically model the indoor climate and energy consumption for heating ventilation and air conditioning (HVAC). However, the proposed OB window opening models are often biased towards the over-represented class where windows remained closed. In addition, they require tuning for each occupant which can not be efficiently scaled to the increased number of occupants. This paper presents a window opening model for commercial buildings using deep learning methods. The model is trained using data from occupants from an office building in Germany. In total the model is evaluated using almost 20 mio. data points from 3 independent buildings, located in Aachen, Frankfurt and Philadelphia. Eventually, the results of 3100 core hours of model development are summarized, which makes this study the largest of its kind in window states modeling. Additionally, the practical potential of the proposed model was tested by incorporating it in the Modelica-based thermal building simulation. The resulting evaluation accuracy and F1 scores on the office buildings ranged between 86-89 % and 0.53-0.65 respectively. The performance dropped around 15 % points in case of sparse input data, while the F1 score remained high.


          Deep Learning on Low-Resource Datasets. (arXiv:1807.03697v1 [cs.LG])      Cache   Translate Page   Web Page Cache   

Authors: Veronica Morfi, Dan Stowell

In training a deep learning system to perform audio transcription, two practical problems may arise. Firstly, most datasets are weakly labelled, having only a list of events present in each recording without any temporal information for training. Secondly, deep neural networks need a very large amount of labelled training data to achieve good quality performance, yet in practice it is difficult to collect enough samples for most classes of interest. In this paper, we propose factorising the final task of audio transcription into multiple intermediate tasks in order to improve the training performance when dealing with this kind of low-resource datasets. We evaluate three data-efficient approaches of training a stacked convolutional and recurrent neural network for the intermediate tasks. Our results show that different methods of training have different advantages and disadvantages.


           Nvidia's new AI takes a one-stop approach to fixing grainy photos       Cache   Translate Page   Web Page Cache   

The Noise2Noise AI image-enhancing technology was developed by researchers from NVIDIA, MIT and Finland’s Aalto University#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

If you've ever taken a photo in low light you've probably encountered the grainy effect that can dilute the finished product. A new AI tool could prove an incredibly easy way to remove this so-called noise, with the ability to automatically produce a clean image after analyzing only the corrupted version.

.. Continue Reading Nvidia's new AI takes a one-stop approach to fixing grainy photos

Category: Digital Cameras

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          Deep Fingerprinting: Undermining Website Fingerprinting Defenses with Deep Learning. (arXiv:1801.02265v4 [cs.CR] UPDATED)      Cache   Translate Page   Web Page Cache   

Authors: Payap Sirinam, Mohsen Imani, Marc Juarez, Matthew Wright

Website fingerprinting enables a local eavesdropper to determine which websites a user is visiting over an encrypted connection. State-of-the-art website fingerprinting attacks have been shown to be effective even against Tor. Recently, lightweight website fingerprinting defenses for Tor have been proposed that substantially degrade existing attacks: WTF-PAD and Walkie-Talkie. In this work, we present Deep Fingerprinting (DF), a new website fingerprinting attack against Tor that leverages a type of deep learning called convolution neural networks (CNN) with a sophisticated architecture design, and we evaluate this attack against WTF-PAD and Walkie-Talkie. The DF attack attains over 98% accuracy on Tor traffic without defenses, better than all prior attacks, and it is also the only attack that is effective against WTF-PAD with over 90% accuracy. Walkie-Talkie remains effective, holding the attack to just 49.7% accuracy. In the more realistic open-world setting, our attack remains effective, with 0.99 precision and 0.94 recall on undefended traffic. Against traffic defended with WTF-PAD in this setting, the attack still can get 0.96 precision and 0.68 recall. These findings highlight the need for effective defenses that protect against this new attack and that could be deployed in Tor.


          Towards Arbitrary Noise Augmentation - Deep Learning for Sampling from Arbitrary Probability Distributions. (arXiv:1801.04211v2 [cs.LG] UPDATED)      Cache   Translate Page   Web Page Cache   

Authors: Felix Horger, Tobias Würfl, Vincent Christlein, Andreas Maier

Accurate noise modelling is important for training of deep learning reconstruction algorithms. While noise models are well known for traditional imaging techniques, the noise distribution of a novel sensor may be difficult to determine a priori. Therefore, we propose learning arbitrary noise distributions. To do so, this paper proposes a fully connected neural network model to map samples from a uniform distribution to samples of any explicitly known probability density function. During the training, the Jensen-Shannon divergence between the distribution of the model's output and the target distribution is minimized. We experimentally demonstrate that our model converges towards the desired state. It provides an alternative to existing sampling methods such as inversion sampling, rejection sampling, Gaussian mixture models and Markov-Chain-Monte-Carlo. Our model has high sampling efficiency and is easily applied to any probability distribution, without the need of further analytical or numerical calculations.


          On Generation of Adversarial Examples using Convex Programming. (arXiv:1803.03607v3 [cs.LG] UPDATED)      Cache   Translate Page   Web Page Cache   

Authors: Emilio Rafael Balda, Arash Behboodi, Rudolf Mathar

It has been observed that deep learning architectures tend to make erroneous decisions with high reliability for particularly designed adversarial instances. In this work, we show that the perturbation analysis of these architectures provides a framework for generating adversarial instances by convex programming which, for classification tasks, is able to recover variants of existing non-adaptive adversarial methods. The proposed framework can be used for the design of adversarial noise under various desirable constraints and different types of networks. Moreover, this framework is capable of explaining various existing adversarial methods and can be used to derive new algorithms as well. Furthermore, we make use of these results to obtain novel algorithms. Experiments show the competitive performance of the obtained solutions, in terms of fooling ratio, when benchmarked with well-known adversarial methods.


          A Compact Network Learning Model for Distribution Regression. (arXiv:1804.04775v3 [cs.LG] UPDATED)      Cache   Translate Page   Web Page Cache   

Authors: Connie Kou, Hwee Kuan Lee, Teck Khim Ng

Despite the superior performance of deep learning in many applications, challenges remain in the area of regression on function spaces. In particular, neural networks are unable to encode function inputs compactly as each node encodes just a real value. We propose a novel idea to address this shortcoming: to encode an entire function in a single network node. To that end, we design a compact network representation that encodes and propagates functions in single nodes for the distribution regression task. Our proposed Distribution Regression Network (DRN) achieves higher prediction accuracies while being much more compact and uses fewer parameters than traditional neural networks.


          Nvidia sfrutta l’intelligenza artificiale per rimuovere grana e filigrane dalle foto      Cache   Translate Page   Web Page Cache   

rimuovere filigrane

La filigrana che utility e applicazioni di ritocco varie consentono di creare (es. questa per Mac), è utile per aggiungere elementi quali il copyright, proteggere immagini, indicare l'autore di una foto, incorporare elementi vari proteggendo immagini e video realizzati da artisti, designer e fotografi.

Nvidia potrebbe rendere il lavoro di protezione con la filigrana più complicato per via di un meccanismo che sfrutta l'intelligenza artificiale per rimuovere automaticamente artefatti da una fotografia, comprese diciture e filigrane, indipendentemente da quanto queste siano complesse.

Eliminazione rumore

Sfruttando il deep learning, una tecnica di Machine Learning che utilizza algoritmi in grado di simulare il cervello umano per apprendere e svolgere una determinata attività, ricercatori di Nvidia, del MIT e della finlandese Università Aalto, sono riusciti ad addestrare un’intelligenza artificiale a rimuovere rumore digitale, l'effetto grana e altri artefatti visivi dopo uno studio che ha messo a confronto due differenti versioni di una foto. Dopo cinquantamila campioni, l'AI ha capito come funziona il meccanismo, imparando a ripulire le foto meglio di un esperto di fotoritocco con anni di esperienza alle spalle.

https://youtu.be/pp7HdI0-MIo

Vari i possibili campi di applicazione: dalla pulizia automatica del rumore nelle foto di cieli stellati scattate con lunghe esposizioni, fino ad applicazioni nel campo dell'imaging a risonanza magnetica che richiede lunghi lavori di post-produzione per arrivare alla diagnostica partendo da rilevamento, la stadiazione e la localizzazione. Tra gli aspetti negativi di questa tecnica che sfrutta l'intelligenza artificiale, la facilità con la quale sarà possibile rimuovere watermak dalle foto, vanificando lo sforzo di chi spera in una protezione per il proprio lavoro. A questo indirizzo, i dettagli tecnici.

 

- Click qui per l'articolo originale con commenti >> Nvidia sfrutta l’intelligenza artificiale per rimuovere grana e filigrane dalle foto


          Comment on How to Develop a Deep Learning Photo Caption Generator from Scratch by Jason Brownlee      Cache   Translate Page   Web Page Cache   
Are you able to confirm that your libraries are up to date?
          Comment on How to Use Word Embedding Layers for Deep Learning with Keras by Jason Brownlee      Cache   Translate Page   Web Page Cache   
You must know the words you want to support at training time. Even if you have to guess. To support new words, you will need a new model.
          Comment on Use Keras Deep Learning Models with Scikit-Learn in Python by Jason Brownlee      Cache   Translate Page   Web Page Cache   
Here is an example: https://machinelearningmastery.com/display-deep-learning-model-training-history-in-keras/
          Comment on Save and Load Your Keras Deep Learning Models by Jason Brownlee      Cache   Translate Page   Web Page Cache   
Yes, in theory I don't see why you couldn't write some python code to use the weights in a saved h5 to make predictions. This would be very easy for an MLP, and some work for other network types. I have not done this, so this is just an off-the-cuff opinion. I have done this for regression models from statsmodels before with great success.
          Comment on How to Develop a Deep Learning Photo Caption Generator from Scratch by Fathi      Cache   Translate Page   Web Page Cache   
Here the part of my code where I have a problem : size = 64 img1 = load_img('00598546-9.jpg', target_size=(1, size, size)) imshow(img1) X1 = (TimeDistributed(Conv2D(32, (3,3), activation='relu'), input_shape=(None, size, size, 3)))(img1) Error message: ayer time_distributed_11 was called with an input that isn't a symbolic tensor. Received type: . Full input: []. All inputs to the layer should be tensors. I'm looking to find the output X1 by using (img1) as an input but I get this error message. How can I use (img1) to find the output ?
          DEEP LEARNING / COMPUTER VISION ENGINEER - 1912197157      Cache   Translate Page   Web Page Cache   
TX-Irving, Job Code – DEEP LEARNING / COMPUTER VISION ENGINEER Work Location: 600 Hidden Ridge Irving Texas 75038 Positions Requested - 1 Hours per Day - 8 Hours per Week - 40 Total Hours – 12 months initially (possible up to 30 months) The Computer Vision team at Environment is looking to add a Deep Learning / Computer Vision Engineer to a highly talented lean agile group of computer vision engineers and pr
          Watch out, video surveillance is intelligent now      Cache   Translate Page   Web Page Cache   
There will now be no escaping the hawk-eye of video surveillance in public places, thanks to new technology that incorporates deep learning features, ...
          NVIDA desenvolve IA capaz de reconstruir fotos sem referencial      Cache   Translate Page   Web Page Cache   

Um estudo conjunto realizado pela NVIDIA, pelo MIT e pela Universidade de Aalto conseguiu encontrar uma forma de recuperar fotografias sem precisar utilizar uma versão limpa da foto alvo. Em outras palavras, a nova IA consegue reconstruir a foto sem nunca ter visto a imagem original.

O resultado foi obtido por meio de um aprendizado de máquina específico identificado como deep learning. Trabalhando com modelagens de alto nível e com várias camadas de processamento, os pesquisadores puderam treinar a IA para que consertasse imagens com diversas formas de “ruídos”, incluindo fotos pixelizadas, com distorções variadas ou mesmo sobrepostas por texto (conforme mostra o vídeo abaixo). O processo leva apenas alguns milissegundos e, não raro, produziu resultados mais nítidos do que os da imagem original.

Embora esforços semelhantes já tenham conseguido, por exemplo, reconstruir fotografias em que faltassem traços faciais, a criação da NVIDIA e do MIT é a primeira capaz de produzir uma imagem limpa exclusivamente a partir de dados corrompidos – ou de duas fotos igualmente manchadas ou de baixa resolução.

Apesar de ter aplicação potencial em diversos campos, a nova inteligência artificial deve encontrar aplicação imediata na medicina diagnóstica. Por exemplo, para tornar mais nítidas imagens providas por exames de ressonância magnética.


          Anomaly Detection and Diagnosis from System Logs Through Deep Learning [pdf]      Cache   Translate Page   Web Page Cache   
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          Software Architect - Java/Android      Cache   Translate Page   Web Page Cache   
CA-San Carlos, Based in Redwood City, we offer devices featuring advanced AI and deep learning that enhances the quality of life by delivering information and performing tasks through audio and visual interactions. Currently, we are looking to bring on a Software Architect who has strong Java and Android SDK experience. If you would like to design the framework of our software and lead a team of software enginee
          USPSTF dismisses CAC for heart disease risk assessment      Cache   Translate Page   Web Page Cache   
The U.S. Preventive Services Task Force (USPSTF) has reaffirmed its recommendation...Read more on AuntMinnie.comRelated Reading: USPSTF rejects adding new risk factors for heart disease Deep learning can quantify CAC on low-dose CT CT CAC scoring tops age for predicting heart disease risk JACC: CT CAC scoring helps screen for CAD Coronary calcium predicts events, death, in younger adults (Source: AuntMinnie.com Headlines)
          University Recruiter (Contract) - Intel - Hillsboro, OR      Cache   Translate Page   Web Page Cache   
Inside this Business Group. High level understanding of AI, Deep Learning, Machine Learning, etc. Regularly monitor candidate pipeline activity and share...
From Intel - Wed, 20 Jun 2018 10:37:58 GMT - View all Hillsboro, OR jobs
          Different Schools of Thought: How Silicon Valley Teaches Robots      Cache   Translate Page   Web Page Cache   
When robots need a brain, their creators turn to Silicon Valley. Most of the AI tech that drives advanced robotics originates in Bay Area labs. At last month's ReWork Deep Learning for Robotics Summit in San Francisco, researchers from Silicon Valley AI labs and institutes discussed their latest work and how it is being used to teach robots. Synced was onsite to bring you an inside look at their work.
          AI Senior Analyst      Cache   Translate Page   Web Page Cache   
Techno-Functional analyst who have hands-on experience in NLP (Natural Language Processing) ML (Machine Learning) Speech Recognition Neural Networks and Deep Learning coding (more) p Login for more job information and to Apply
          Lee County Property Appraiser's Office Turns to Pushpin Change...      Cache   Translate Page   Web Page Cache   

Pushpin leverages deep learning to accelerate parcel change detection and increase accuracy

(PRWeb July 11, 2018)

Read the full story at https://www.prweb.com/releases/2018/07/prweb15617331.htm


          Watch As NVIDIA Noise2Noise AI Magically Fixes Grainy Photos With Deep Learning      Cache   Translate Page   Web Page Cache   
Watch As NVIDIA Noise2Noise AI Magically Fixes Grainy Photos With Deep Learning It’s happened to us all at some point in time — you capture an image in less-than-ideal light conditions and the end result is a is grainy photo filled with digital noise. While you may still be able to make out many of the details in the photograph, wouldn’t it be nice if you could somehow magically restore it to near perfect condition the

          Research Engineer WANTED | Develop solutions to improve robotic systems! by V3 Smart Technologies Pte Ltd      Cache   Translate Page   Web Page Cache   
Calling all computer science/ computer engineering graduates! Do you seek to work in a dynamic environment and apply your knowledge to develop research driven solutions? V3 is expanding! As our next research engineer, you will be involved in the following: - Research & Develop SLAM, Heuristics Algorithms and/or AI in path planning, routing & optimisation - Research & Develop Vision Intelligence using Deep Learning and AI; - Analyse, integrate robotics into non-automated machines; - Conduct research into the feasibility, design, operate and performance of robotic mechanisms; - Evaluate and develop solutions to improve the existing robotic system (electrical, electronic, mechanical); - Develop firmware for the electronics; - Investigate system failures; - Process or interpret signals and sensor data We are looking for an individual with the following qualities: - Bachelor, Masters or PhD in Computer Science and Computer Engineering - Have a passion in Algorithms and AI - Knowledge in SLAM and ROS - Be able to work independently Sounds like your line of work? Click "Want to Visit" to apply and chat with us :) Remember to brush up your Wantedly profile so that we can get to know you better!
          Comment on How to Use Word Embedding Layers for Deep Learning with Keras by abbas      Cache   Translate Page   Web Page Cache   
where can i find the file "../glove_data/glove.6B/glove.6B.100d.txt"??because i come up with the following error. File "", line 36 f = open(‘../glove_data/glove.6B/glove.6B.100d.txt’) ^ SyntaxError: invalid character in identifier
          Comment on How to Grid Search Hyperparameters for Deep Learning Models in Python With Keras by Kemas Farosi      Cache   Translate Page   Web Page Cache   
Hi Jason, Great tutorial, I have a question, is it possible to find how many hidden layers in my deep neural networks by grid search ? because i want to find the best layer numbers in my DNN. thanks
          Object Detection and Recognition Using Deep Learning in OpenCV      Cache   Translate Page   Web Page Cache   
скачать Object Detection and Recognition Using Deep Learning in OpenCV бесплатно
Название: Object Detection and Recognition Using Deep Learning in OpenCV
Автор: Param Uttarwar
Страниц: Duration: 2h 17m
Формат: HDRip
Размер: 570,7 mb
Качество: Отличное
Язык: Английский
Жанр: Video Course
Год издания: 2018


Skill up with techniques for detection and decoding of images in OpenCV


          This Week in Genome Biology      Cache   Translate Page   Web Page Cache   
The method brings together on- and off-target sgRNA predictions into a deep learning framework that compared favorably with alternative in silico ...
          Using Artificial Intelligence to Study Wild Animals      Cache   Translate Page   Web Page Cache   
The latest study sees researchers introduce the power of deep learning to a new domain—ecology. A collaborative team of scientists from Harvard, ...
          AI Flood Drives Chips to the Edge      Cache   Translate Page   Web Page Cache   
Since then, web giants such as Amazon, Google, and Facebook have started applying deep learning to video, speech, and translation. Last year ...
          NVIDIA Uses AI to Banish Noise from Images      Cache   Translate Page   Web Page Cache   
As NVIDIA explains, typical deep learning approaches have required training a neural network to recognize when a clean end state image should look ...
          Alphabet’s Verily forms joint venture with ResMed to study sleep apnea      Cache   Translate Page   Web Page Cache   
Google uses AI, deep learning to predict cardiovascular risk from retina ... Google's deep learning algorithm could more accurately detect a patient's ...
          A deep neural network is being harnessed to analyse nuclear events      Cache   Translate Page   Web Page Cache   
These findings are generated by the utilisation of deep learning in order to teach and program machines and systems to learn and make decisions ...
          deep learning      Cache   Translate Page   Web Page Cache   
It could be a dream for music sampling as MIT reveal their new tech capable of finding and editing individual instruments from tracks. When a track is ...
          Position and Proximity Sensors Market Valuation of US $13,626.7 Mn by the End of 2026: MarketResearchReports.Biz      Cache   Translate Page   Web Page Cache   

Recent research and the current scenario as well as future market potential of "Position and Proximity Sensors Market - Global Industry Analysis, Size, Growth, Trends, Share and Forecast 2017 - 2026" globally.

Albany, NY -- (SBWIRE) -- 07/11/2018 -- The global position and proximity sensors market is projected to exhibit a CAGR of 5.5% over the course of the forecast period. The market is likely to cross a valuation of US$13,626.7 Mn by the end of 2026.

A new report on position and proximity sensors provides perceptive insights on the chronological growth flight of the market along with the future prospects and present scenario of the market. The report offers an exclusive analysis of the global market and also presents insights on regional and other segments.

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Position and Proximity Sensors Market: Overview

The report offers a complete summation of the market including an official abstract that draws out the centre examples progressing in the market. It also discusses on a couple of facets, for example, drivers, obstacles, and predictions that have been found in the global market. It also acquaints readers with figures related to volume, value, and development rate of the market from a growth point of view. With reverence to market breakdown, each segment is analysed and presented in the report. It also gives an assessment in light of the market condition, and moreover presents a value chain analysis of the products and applications in concern. A year to year evolution of the market has likewise been offered in the report for the reader to be predominantly aware of the altering scenario of the market.

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The report is the end result of the cautious research work of the market analysts employing reliable sources. The information introduced has been studied carefully by industry experts of TMR. The data that has been presented here has been assembled from various tried and tested sources. The figures have also been checked by the analysts and can be used to settle on key decisions and formulate strategies.

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           L'intelligenza artificiale NVidia corregge le foto affette da rumore digitale       Cache   Translate Page   Web Page Cache   
È capitato praticamente a tutti: scattando una foto in condizioni di luce scarsa l'immagine appare affetta da un evidente problema. Essa appare 'granulosa', rovinata dalla presenza di una miriade di puntini (il cosiddetto 'rumore digitale').
Nelle situazioni peggiori diventa addirittura difficoltoso riconoscere il soggetto ritratto nella foto.

I tecnici di NVidia, di concerto con i ricercatori del MIT e gli accademici della Aalto University hanno messo a punto un sistema chiamato Noise2Noise in grado di restaurare l'immagine rimuovendo ogni traccia del rumore digitale.

Per raggiungere l'ambizioso traguardo i ricercatori hanno usato una batteria di GPU NVidia Tesla P100 e il framework per il deep learning TensorFlow accelerato mediante l'utilizzo delle librerie cuDNN (CUDA Deep Neural Network), esattamente come fatto ad aprile scorso: NVidia ricostruisce le immagini danneggiate grazie all'intelligenza artificiale.


Addestrando la rete neurale con oltre 50.000 immagini provenienti dai database ImageNet (la base dati contiene sia l'immagine affetta dal rumore digitale che la versione esente da difetti), l'intelligenza artificiale così messa a punto è stata poi in grado di correggere anche le foto più problematiche.

Noise2Noise è stato in grado di riconoscere i soggetti ritratti in ciascuna immagine e di agire di conseguenza applicando le correzioni fotografiche migliori.
           Nvidia's new AI takes a one-stop approach to fixing grainy photos       Cache   Translate Page   Web Page Cache   

The Noise2Noise AI image-enhancing technology was developed by researchers from NVIDIA, MIT and Finland’s Aalto University#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

If you've ever taken a photo in low light you've probably encountered the grainy effect that can dilute the finished product. A new AI tool could prove an incredibly easy way to remove this so-called noise, with the ability to automatically produce a clean image after analyzing only the corrupted version.

.. Continue Reading Nvidia's new AI takes a one-stop approach to fixing grainy photos

Category: Digital Cameras

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          NVIDIA AI that can remove noise and text from photos      Cache   Translate Page   Web Page Cache   
Researchers from NVIDIA, Aalto University, and MIT developed a deep learning based method that can fix photos by simply looking at examples of corrupted photos only.    ...
          NVIDIA entfernt Wasserzeichen und Bildrauschen mit einer KI      Cache   Translate Page   Web Page Cache   
Mit einem neuen Deep Learning-Verfahren möchte NVIDIA verrauschte oder mit Text oder Wasserzeichen überlagerte Fotos in deutlich besserer Qualität als bisher möglich wiederherstellen.
          University Recruiter (Contract) - Intel - Hillsboro, OR      Cache   Translate Page   Web Page Cache   
Inside this Business Group. High level understanding of AI, Deep Learning, Machine Learning, etc. Regularly monitor candidate pipeline activity and share...
From Intel - Wed, 20 Jun 2018 10:37:58 GMT - View all Hillsboro, OR jobs
          Watch As NVIDIA Noise2Noise AI Magically Fixes Grainy Photos With Deep Learning      Cache   Translate Page   Web Page Cache   
Watch As NVIDIA Noise2Noise AI Magically Fixes Grainy Photos With Deep Learning It’s happened to us all at some point in time — you capture an image in less-than-ideal light conditions and the end result is a is grainy photo filled with digital noise. While you may still be able to make out many of the details in the photograph, wouldn’t it be nice if you could somehow magically restore it to near perfect condition the
          Purchase to pay v3      Cache   Translate Page   Web Page Cache   
English
Field Group: 
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P2P SOLUTIONS FOR THE FULLY NETWORKED ENTERPRISE

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Esker’s cloud-based, AI-powered platform spans the entire P2P process, equipping finance departments with the speed, strategy, and support they need to improve purchasing and vendor decisions.

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Purchasing
Supplier Information Management
Ensure a global view of customers’ behavior, from orders to invoices.
Contract Management
Drive new savings with improved contract visibility and compliance.
Procurement
Transform buying into an Amazon-like experience across the enterprise.
Accounts Payable
AP Automation
Reduce invoicing costs and delays thanks to AI-based data extraction.
Expense Management
Free up your finance team by automating hours of low-value admin tasks.
Payment & Supply Chain Financing
Automate payment approval workflow while securing early-pay discounts.

 

 

 

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Esker named “innovative p2p technology of the year” winner
PayStream Advisors Innovate Awards – 2016
 
“Parts Town needed solutions that put us in a position to continue growth. Providing excellent customer service was the driving force behind our decision to partner with Esker, and we are now able to provide an improved process from start to finish.”
AMY ARGENTINE, DIRECTOR OF TECHNICAL SERVICE, PARTS TOWN
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Challenges we help our customers solve

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This isn’t our first rodeo. If there’s a procure-to-pay problem that needs solving, chances are Esker has a solution for it, including:

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  • Lengthy or delayed cycle times
  • Maverick buying & fraudulent transactions
  • Late or inaccurate closings
  • Missed early payment discounts
  • Late payment fees
  • Matching orders & receipts
  • Difficult vendor negotiations
  • Rushing to place orders
  • Disparate systems & processes
  • Lack of compliance & governance
  • Limited visibility throughout the entire cycle
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“Esker has greatly improved our daily work — we never have to worry about inquiries from within our organization, or externally, from customers or suppliers. Using the dashboard, we can see pending invoices, monitor operations and check any outstanding invoices.″
Senior P2P Administrator │ HEINEKEN China
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Paralax effect with partnership spirit
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Esker’s P2P Expertise

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Compliance & Security
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From fraud detection to eliminating duplicate payments to enforcing financial policies, Esker’s compliance and security standards in the purchase-to-pay process include:

  • ISO 27001:2013
  • SSAE 18 & ISAE 3402
  • HIPAA & the HITECH Act
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VISIBILITY & ANALYTICS
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When P2P documents go through Esker, the data is instantly accessible via built-in dashboards. Users can choose what KPIs are displayed on their interface to:

  • Prioritize daily tasks & documents
  • Monitor team & individual performance
  • Review & approve documents on the go
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ARTIFICIAL INTELLIGENCE
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Built from technologies designed to mimic human intelligence, Esker’s AI Engine helps businesses make fast and intelligent cash management decisions using:

  • Logic & rules
  • Decision trees
  • Machine learning & deep learning
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GLOBAL PLATFORM
Persona Block Text: 

Esker offers a single, collaborative and cloud-based platform to automate the order-to-cash cycle and grow without operational restraints thanks to:

  • Universal access (cloud, mobile, desktop)
  • Multi-tenant, operating on MS Azure, AWS, etc.
  • Worldwide multi-ERP integration
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Ask us anything

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Questions about Esker’s P2P solutions? We’re here to help and ready when you are.

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PURCHASE-TO-PAY AUTOMATION
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Transforming the way businesses purchase, book and pay

Request a demo

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You’re in good company. Explore some of the other companies and AP leaders that have benefited from automating their processes with Esker.
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