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Deep Learning Economies of Scale: How Real-World Computer Vision is Changing

This article was originally published by BDTI. It is reprinted here with the permission of BDTI. When we launched the Embedded Vision Alliance in 2011, we did so out of the conviction that computer vision was ready to become a ubiquitous technology that would be used to solve numerous important, real-world problems. And, indeed, it’s […]

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Types of Tracking Defined: Skeletal Tracking, Gestures, Object Tracking and More

This blog post was originally published at Intel's website. It is reprinted here with the permission of Intel. When talking about computer vision, the word “tracking” comes up a lot. There are a lot of different kinds of tracking, depending on what you are tracking, how you are tracking it, and what you’re trying to

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Accelerating AI Performance in an Open Software Ecosystem

This blog post was originally published at Codeplay Software's website. It is reprinted here with the permission of Codeplay Software. In the latest White Paper from the Linley Group, Linley Gwennap examines how an open software ecosystem is critical to enable developers to write artificial intelligence software that takes full advantage of the latest processors.

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Image Processing and Computer Vision in One Package: A Logical Next Step

Computer vision on the edge is a good start but it isn’t enough. It needs to deal with distorted images from wide-angle lenses, image stabilization, low-light conditions and other imaging functions we already see in more advanced applications. And it has to continue to do so at low cost and low power. Consumers and businesses

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Hollywood and the Ncam Mk2 Camera Bar with Intel® RealSense™ Technology

This blog post was originally published at Intel's website. It is reprinted here with the permission of Intel. In recent years, visual effects in movies and television have grown both more sophisticated and more ubiquitous. Audiences have grown used to elaborate environments and fantastical fight scenes, historical dramas and futuristic worlds. As audiences expect more,

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Case Study: ResNet50 with DALI

This blog post was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. Let’s imagine a situation. You buy a brand-new, cutting-edge, Volta-powered DGX-2 server. You’ve done your math right, expecting a 2x performance increase in ResNet50 training over the DGX-1 you had before. You plug it into your rack

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