Videos

“Image Sensors for Vision: Foundations and Trends,” a Presentation from ON Semiconductor

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Robin Jenkin, Director of Analytics, Algorithm and Module Development at ON Semiconductor, presents the "Image Sensors for Vision: Foundations and Trends" tutorial at the May 2016 Embedded Vision Summit. Choosing the right sensor, lens and system configuration is crucial to setting you off in the right direction for your vision application. Jenkin examines fundamental considerations […]

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“Understanding Camera Subsystems for Your Embedded Vision System and Making the Right Choice,” a Presentation from Basler

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Gerrit Fischer, Head of Product Market Management at Basler, presents the "Understanding Camera Subsystems for Your Embedded Vision System and Making the Right Choice" tutorial at the May 2016 Embedded Vision Summit. More than ever, you have a wide range of camera subsystems to choose from. At one end of the spectrum, a system designer

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“Efficient Convolutional Neural Network Inference on Mobile GPUs,” a Presentation from Imagination Technologies

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Paul Brasnett, Principal Research Engineer at Imagination Technologies, presents the "Efficient Convolutional Neural Network Inference on Mobile GPUs" tutorial at the May 2016 Embedded Vision Summit. GPUs have become established as a key tool for training of deep learning algorithms. Deploying those algorithms on end devices is a key enabler to their commercial success and

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“Accelerating Deep Learning Using Altera FPGAs,” a Presentation from Intel

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Bill Jenkins, Senior Product Specialist for High Level Design Tools at Intel, presents the "Accelerating Deep Learning Using Altera FPGAs" tutorial at the May 2016 Embedded Vision Summit. While large strides have recently been made in the development of high-performance systems for neural networks based on multi-core technology, significant challenges in power, cost and, performance

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“Fast Deployment of Low-power Deep Learning on CEVA Vision Processors,” a Presentation from CEVA

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Yair Siegel, Director of Segment Marketing at CEVA, presents the "Fast Deployment of Low-power Deep Learning on CEVA Vision Processors" tutorial at the May 2016 Embedded Vision Summit. Image recognition capabilities enabled by deep learning are benefitting more and more applications, including automotive safety, surveillance and drones. This is driving a shift towards running neural

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“Lessons Learned from Bringing Mobile and Embedded Vision Products to Market,” a Presentation from ARM

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Tim Hartley, Product Manager in the Personal Mobile Compute Business Line at ARM, presents the "Lessons Learned from Bringing Mobile and Embedded Vision Products to Market" tutorial at the May 2016 Embedded Vision Summit. Great news: technology is finally at a point where we can build sophisticated computer vision applications that run on mass market

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“Making Computer Vision Software Run Fast on Your Embedded Platform,” a Presentation from Luxoft

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Alexey Rybakov, Senior Director at Luxoft, presents the "Making Computer Vision Software Run Fast on Your Embedded Platform" tutorial at the May 2016 Embedded Vision Summit. Many computer vision algorithms perform well on desktop class systems, but struggle on resource constrained embedded platforms. This how-to talk provides a comprehensive overview of various optimization methods that

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“Real-world Vision Systems Design: Challenges and Techniques,” a Presentation from Intel

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Yury Gorbachev, Principal Engineer at Itseez (now part of Intel), presents the "Real-world Vision Systems Design: Challenges and Techniques" tutorial at the May 2016 Embedded Vision Summit. Computer vision is central to many modern, cool products and technologies, including augmented reality, virtual reality and drones. Thanks to recent advances in system-on-chip and embedded systems design,

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“The Road Ahead for Neural Networks: Five Likely Surprises,” a Presentation from Cadence

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Dr. Chris Rowen, Chief Technology Officer of the IP Group at Cadence, presents the "Road Ahead for Neural Networks: Five Likely Surprises" tutorial at the May 2016 Embedded Vision Summit. Cognitive computing is finally getting real! It has passed through the phases of obscurity and curiosity and is surviving the current phase of breathless hype.

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“TensorFlow: Enabling Mobile and Embedded Machine Intelligence,” a Presentation from Google

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Pete Warden, Research Engineer at Google, presents the "TensorFlow: Enabling Mobile and Embedded Machine Intelligence" tutorial at the May 2016 Embedded Vision Summit. Following a brief overview of the advances in deep learning and AI over the last few years, Pete discusses how Google uses TensorFlow to deploy those advances in products on mobile and

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Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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