Brian Dipert

Optimizing Computer Vision Applications Using OpenCL and GPUs

Algorithms & Models, AMD, Arm, Articles, Imagination Technologies, Processors, Software, Technical Articles, Tools /

The substantial parallel processing resources available in modern graphics processors makes them a natural choice for implementing vision-processing functions. The rapidly maturing OpenCL framework enables the rapid and efficient development of programs that execute across GPUs and other heterogeneous processing elements within a system. In this article, we briefly review parallelism in computer vision applications, […]

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

Algorithms & Models, Edge AI and Vision Alliance, Intel, Software, Tools, Videos /

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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CEV089_CEVA_CDNN2_LRES

CEVA’s 2nd Generation Neural Network Software Framework Extends Support for Artificial Intelligence Including Google’s TensorFlow

News /

CDNN2 supports the most demanding machine learning networks, from pre-trained network to embedded system, including GoogLeNet, VGG, SegNet, Alexnet, ResNet and more. CDNN2 becomes industry’s first software framework for embedded systems to automatically support networks generated by TensorFlow™ Combined with CEVA-XM4 imaging and vision processor, CDNN2 offers highly power-efficient deep learning solution for any camera-enabled

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Developing an Industrial Machine Vision Application: A Free On-Demand Webinar from Mentor Graphics, AMD and Qtechnology

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On June 30 at 9AM PT (12PM ET), Mentor Graphics will present a free hour-long webinar entitled "Developing an Industrial Machine Vision Application", in partnership with fellow Alliance member company AMD and with Qtechnology. Here's the description, from the event page: In Industrial Machine Vision systems there are large classes of problems that require real

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

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

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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VisionSystemsDesign

Industry Standards Simplify Computer Vision Software Development

Blog Posts /

This blog post was originally published at Vision Systems Design's website. It is reprinted here with the permission of PennWell. When developing computer vision software, de facto standards such as the OpenCV open source computer vision library (which I mentioned in a recent column) are extremely valuable in helping you get your development done quickly

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Deep Learning on Mobile Devices at the Embedded Vision Summit 2016

Articles, Imagination Technologies, Technical Articles /

This article was originally published at Imagination Technologies' website. It is reprinted here with the permission of Imagination Technologies. It was clear last week at the annual Embedded Vision Summit in Santa Clara that the time of computer vision and deep learning on mobile had finally arrived. Interest in the area is growing noticeably –

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

Algorithms & Models, Edge AI and Vision Alliance, Processors, Software, Tools, Videos /

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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Video Stabilization Using Computer Vision: Tips and Insights From CEVA’s Experts

Articles, Ceva, Technical Articles /

This article was originally published at CEVA's website. It is reprinted here with the permission of CEVA. Demand is on the rise for video cameras on moving platforms. Smartphones, wearable devices, cars, and drones are all increasingly employing video cameras with higher resolution and higher frames rates. In all of these cases, the captured video

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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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