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BDTI Demonstration of Neural Network-Based Object Detection

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Jeremy Giddings, Director of Business Development at BDTI, demonstrates the company's machine learning engineering services at the May 2017 Embedded Vision Summit. Specifically, Giddings demonstrates BDTI’s ability to design, train, and implement neural networks for specific use cases. For this demo, BDTI engineers implemented YOLO (You Only Look Once), an approach in which classification and […]

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Visual Intelligence Opportunities in Industry 4.0

Algorithms, AMD, Articles, Basler, Edge AI and Vision Alliance, Industrial Vision (Computer Vision), MVTec, Processors, Sensors and Cameras, Software, Technical Articles, Tools /

In order for industrial automation systems to meaningfully interact with the objects they're identifying, inspecting and assembling, they must be able to see and understand their surroundings. Cost-effective and capable vision processors, fed by depth-discerning image sensors and running robust software algorithms, continue to transform longstanding industrial automation aspirations into reality. And, with the emergence

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Allied Vision Demonstration of Object and Color Recognition Using the 1 Product Line Camera Series

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Felix Nikolaus, Firmware Designer at Allied Vision, demonstrates the company's latest embedded vision technologies and products at the May 2017 Embedded Vision Summit. Specifically, Nikolaus demonstrates Allied Vision’s all-new 1 Product Line camera series. He explains how the 130 C-500, equipped with MIPI CSI-2, can be paired with a Nitrogen6_MAX i.MX6 processor board running on

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JetPack 3.1 Doubles Jetson’s Low-Latency Inference Performance

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Today, NVIDIA released JetPack 3.1, the production Linux software release for Jetson TX1 and TX2. With upgrades to TensorRT 2.1 and cuDNN 6.0, JetPack 3.1 delivers up to a 2x increase in deep learning inference performance for real-time applications like vision-guided navigation and motion control, which benefit from accelerated batch size 1. The improved features

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Software Frameworks and Toolsets for Deep Learning-based Vision Processing

Algorithms, AMD, Articles, Au-Zone Technologies, BDTI, Edge AI and Vision Alliance, MVTec, Processors, Software, Synopsys, Technical Articles, Tools /

This article provides both background and implementation-detailed information on software frameworks and toolsets for deep learning-based vision processing, an increasingly popular and robust alternative to classical computer vision algorithms. It covers the leading available software framework options, the root reasons for their abundance, and guidelines for selecting an optimal approach among the candidates for a

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Embedded Vision Insights: July 6, 2017 Edition

Edge AI and Vision Alliance, Newsletters /

LETTER FROM THE EDITOR Dear Colleague, TensorFlow has become a popular framework for creating machine learning-based computer vision applications, especially for the development of deep neural networks. If you’re planning to develop computer vision applications using deep learning and want to understand how to use TensorFlow to do it, then don’t miss next Thursday's full-day,

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July 12, 2017 Webinar

Thank you for attending the July 12, 2017 webinar "OpenCV on Zynq: Accelerating 4k60 Dense Optical Flow and Stereo Vision," presented by Xilinx and organized by the Embedded Vision Alliance! For more information on Xilinx's reVISION stack, please visit https://www.xilinx.com/reVISION. For more information on OpenCV and other computer vision topics, please visit the Embedded Vision

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Synopsys Embedded Vision Processor IP Quadruples Neural Network Performance for Machine Learning Applications

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Enhanced DesignWare EV6x Family Delivers Up to 4.5 TeraMACs/sec for Real-Time Vision Processing MOUNTAIN VIEW, Calif., June 26, 2017 /PRNewswire/ — Highlights: DesignWare EV6x Vision Processors integrate up to four 512-bit vector DSPs and a CNN engine, providing scalable performance for a wide range of current and emerging embedded vision applications The EV6x processors, with

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Embedded Vision Insights: June 20, 2017 Edition

Edge AI and Vision Alliance, Newsletters /

LETTER FROM THE EDITOR Dear Colleague, TensorFlow has become a popular framework for creating machine learning-based computer vision applications, especially for the development of deep neural networks. If you’re planning to develop computer vision applications using deep learning and want to understand how to use TensorFlow to do it, then don’t miss next month's full-day,

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“The Vision Acceleration API Landscape: Options and Trade-offs,” a Presentation from the Khronos Group

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

Neil Trevett, President of the Khronos Group and Vice President at NVIDIA, presents the "Vision Acceleration API Landscape: Options and Trade-offs" tutorial at the May 2017 Embedded Vision Summit. The landscape of APIs for accelerating vision and neural network software using specialized processors continues to rapidly evolve. Many industry-standard APIs, such as OpenCL and OpenVX,

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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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