Brian Dipert

ONSPR2903_KAI08052_LRES

ON Semiconductor Enhances Near-Infrared Performance of CCD Image Sensors

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New 8-megapixel device is first with improved near-infrared sensitivity for machine vision and other applications. PHOENIX, AZ – July 11, 2016 – ON Semiconductor (Nasdaq: ON), driving energy efficient innovations, is enhancing imaging performance in demanding industrial applications with technology that improves the near-infrared sensitivity of CCD image sensors. The 8 megapixel (MP) KAI-08052 image […]

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

Algorithms & Models, Imagination Technologies, Processors, Software, Tools, Videos /

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

Algorithms & Models, Intel, Processors, Software, Tools, Videos /

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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“Deep Learning on Embedded Systems”: A Free Webinar from CEVA

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On July 27 at 1PM ET (10AM PT), CEVA will give a free hour-long webinar entitled "Deep Learning on Embedded Systems". Here's the description, from the event page: As Artificial Intelligence (AI) marches into almost every aspects of our lives, one of the major challenges is bringing this intelligence to small, low-power devices. This requires

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VisionSystemsDesign

Deep Learning for Computer Vision: Perspectives from Algorithm, Market and Processor Experts

Blog Posts /

This blog post was originally published at Vision Systems Design's website. It is reprinted here with the permission of PennWell. Convolutional neural networks (CNNs) and other deep learning techniques are rapidly becoming key enabling technologies for applications requiring object recognition and other computer vision capabilities. I first discussed the topic of deep learning in a

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Embedded Vision Insights: July 7, 2016 Edition

Edge AI and Vision Alliance, Newsletters /

FEATURED VIDEOS "Challenges in Object Detection on Embedded Devices," a Presentation from CEVA As more products ship with integrated cameras, says Adar Paz, Imaging and Computer Vision Team Leader at CEVA, there is an increased potential for computer vision (CV) to enable innovation. For instance, CV can tackle the "scene understanding" problem by first figuring

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

Algorithms & Models, Ceva, Processors, Software, Tools, Videos /

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

Algorithms & Models, Arm, Processors, Sensors and Cameras, Software, Tools, Videos /

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

Algorithms & Models, LUXOFT, Processors, Software, Tools, Videos /

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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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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