Vision


Microsoft Computer Vision APIs Distilled - Programmer Books

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Imagine an app that describes to the visually impaired the objects around them, or reads the Sunday paper, a favorite magazine, or a street sign. Or an app that is capable of monitoring what is happening inside an area without human control, and then makes a decision based on interpreting an occurrence detected with a live camera. This book teaches developers Microsoft's Computer Vision APIs, a service capable of understanding and interpreting the content of an image. Author Del Sole begins by providing a succinct "need to know" overview of the service with descriptions. You then learn from hands-on demonstrations that show how basic C# code examples can be re-used across platforms.


Auriga Attends Intel Experience Day 2019

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Intel Experience Day 2019, organized by Intel, one of the major innovative hardware and technology corporations worldwide, took place in Moscow at the end of October. Intel and partner companies presented the latest Intel hardware and software product implementations advancing IoT, AI, computer vision, machine learning, object recognition, and more. Many speakers shared their ideas and insights on trending industrial innovations like cloud computing, Big Data, and analytics, including Al Diaz, Intel's Vice President, Natalya Galyan, Intel's Regional Director for Russia, and Marina Alekseeva, CEO of R&D of Intel in Russia. Intel Experience Day 2019 attracted many IT market players who use Intel solutions in their work daily, and Auriga experts were among them. Several years ago, Auriga became a pioneer user of the Intel Multi-OS Engine tool to develop an innovative iPad application for patient monitoring.


AiThority Interview with Sasha Apartsin, VP of AI at Harmon.ie

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I started developing AI algorithms for handwriting recognition at my part-time student job while doing my Undergraduate degree in Computer Science. Since then, over the last 20 years or so, I have strived to combine my work in the industry with academic research. I did my Graduate degree in Computer Vision and completed my Ph.D. in Machine Learning while having quite an intensive career in the industry in parallel with my studies. In the industry, I've worked on all kinds of data and applications, including medical imaging, educational multimedia, mobile advertising, financial time series, video, text and speech processing for public safety, and other projects. When I began working with the product and business aspects of R&D, I felt that I needed to strengthen the relevant skills, so I went back to school and got an additional Master's degree in Technology Management.


Internship Opportunities: Computer Vision ai-jobs.net

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Microsoft Research provides a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers. Our researchers and engineers pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment. It has never been a more exciting time at the Computer Vision Group at Microsoft Cloud & AI! We continue to advance the state of the art in the areas we choose to study. The Computer Vision Group is tasked to improve our odds of betting on the "next big thing" and impact various products in the areas of cloud and edge intelligence, such as Microsoft Cognitive Services and HoloLens.


10 Applications of Deep Learning for Computer Vision

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Deep learning models have the ability to learn patterns and to derive meaning from images. Thus, they reduce the need for methods based on hand-crafted features. Deep learning methods are used in a wide range of different computer vision applications such as motion detection, face recognition, and image synthesis. Let's take a look at some of the most popular computer vision applications that are powered by deep learning. Deep learning is widely used in computer vision systems for face recognition tasks.


r/MachineLearning - [R] EfficientDet: Scalable and Efficient Object Detection

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Abstract: Model efficiency has become increasingly important in computer vision. In this paper, we systematically study various neural network architecture design choices for object detection and propose several key optimizations to improve efficiency. First, we propose a weighted bi- directional feature pyramid network (BiFPN), which allows easy and fast multi- scale feature fusion; Second, we propose a compound scaling method that uniformly scales the resolution, depth, and width for all backbone, feature network, and box/class prediction networks at the same time. Based on these optimizations, we have developed a new family of object detectors, called EfficientDet, which consistently achieve an order-of-magnitude better efficiency than prior art across a wide spectrum of resource constraints. In particular, without bells and whistles, our EfficientDet-D7 achieves stateof- the-art 51.0 mAP on COCO dataset with 52M parameters and 326B FLOPS1, being 4x smaller and using 9.3x fewer FLOPS yet still more accurate ( 0.3% mAP) than the best previous detector.


AI and gene-editing pioneers to discuss ethics Stanford News

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Upon meeting for the first time at a dinner at Stanford earlier this year, Fei-Fei Li and Jennifer Doudna couldn't help but note the remarkable parallels in their experiences as scientists. Stanford's Fei-Fei Li and Jennifer Doudna of UC Berkeley will discuss the ethics of artificial intelligence and CRISPR technology. Both women helped kickstart twin revolutions that are profoundly reshaping society in the 21st century – Li in the field of artificial intelligence (AI) and Doudna in the life sciences. Both revolutions can be traced back to 2012, the year that computer scientists collectively recognized the power of Li's approach to training computer vision algorithms and that Doudna drew attention to a new gene-editing tool known as CRISPR-Cas9 ("CRISPR" for short). Both pioneering scientists are also driven by a growing urgency to raise awareness about the ethical dangers of the technologies they helped create.


Ten factors radiologists should consider when selecting AI vendors - Signify Research

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This insight was featured in the November 2019 issue of HealthCare Business News magazine. With over 150 independent software vendors developing machine learning solutions for medical imaging, sorting through the plethora of options to select vendors is a challenge. Here are 10 factors radiologists should consider (and questions they should ask) before partnering with vendors providing AI solutions for medical imaging. The foremost consideration for healthcare providers adopting AI into their clinical workflow is relevancy. Does the AI solution truly address the needs of the healthcare provider, regardless of the associated costs and inconveniences to implement such a solution?



Investorideas.com Newswire - AI News: VSBLTY (CSE: VSBY) (OTC: VSBGF) Launches Two Security Initiatives to Reduce Crime and Make South African Communities Safer

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Newswire) VSBLTY Groupe Technologies Corp. (CSE: VSBY) (5VS.F) (VSBGF), a leading retail software and technology company, announced today that-in partnership with Onyx-Cognivas Pty.-it is launching two privately-led security deployments in South Africa to support community safety initiatives. The state-of-the-art security technology will protect two prominent high-rise residential apartment buildings in the upmarket Sandton area, a high income residential, financial and business suburb of Johannesburg with a population of 225,000. The rollout plan is to deploy this technology across several apartment blocks, a hotel and commercial properties in the precinct-with the objective of deploying a "private Smart City". In addition, advanced custom sensory applications are planned to be installed in a well-known petroleum group with convenience stores/service stations throughout South Africa. The announcement was made by Jay Hutton, VSBLTY co-founder and CEO, who said, "We are excited to provide complete Smart City-like security solutions in Sandton. This state-of-the-art technology uses the power of machine learning and computer vision."