DEEP LEARNING FOR VISION PROCESSING The Caffe2 Framework for Mobile and Embedded Deep Learning Fei Sun, software engineer at Facebook, introduces Caffe2, a new open-source machine learning framework, in this presentation. Sun also explains how Facebook is using Caffe2 to enable computer vision in mobile and embedded devices. Methods for Understanding How Deep Neural Networks […]
Embedded Vision Insights: June 26, 2018 Edition Read More +
Bruce Maxwell, Director of Research at Tandent Vision Science, presents the “A Physics-based Approach to Removing Shadows and Shading in Real Time” tutorial at the May 2018 Embedded Vision Summit. Shadows cast on ground surfaces can create false features and modify the color and appearance of real features, masking important information used by autonomous vehicles,
Lina Karam, Professor and Computer Engineering Director at Arizona State University, presents the “Generative Sensing: Reliable Recognition from Unreliable Sensor Data” tutorial at the May 2018 Embedded Vision Summit. While deep neural networks (DNNs) perform on par with – or better than – humans on pristine high-resolution images, DNN performance is significantly worse than human
Anirudh Koul, Senior Data Scientist, and Jin Yamamoto, Principal Program Manager, both from Microsoft, present the “Infusing Visual Understanding in Cloud and Edge Solutions Using State Of-the-Art Microsoft Algorithms” tutorial at the May 2018 Embedded Vision Summit. Microsoft offers its state-of-the-art computer vision algorithms, used internally in several products, through the Cognitive Services cloud APIs.
Paul Maria Zalewski, Product Line Manager at Allied Vision Technologies, presents the “A New Generation of Camera Modules: A Novel Approach and Its Benefits for Embedded Systems” tutorial at the May 2018 Embedded Vision Summit. Embedded vision systems have typically relied on low-cost image sensor modules with a MIPI CSI-2 interface. Now, machine vision camera
Tuesday, June 19, 2018 — FLIR today announced the upcoming release of a first-of-its-kind, free machine learning thermal dataset for Advanced Driver Assistance Systems (ADAS) and self-driving vehicle researchers, developers, and auto manufacturers. The starter dataset features a compilation of more than 10,000 annotated thermal images of people, cars, other vehicles, bicycles and dogs in
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Radhakrishna Giduthuri, Software Architect at Advanced Micro Devices (AMD), presents the “OpenVX Computer Vision and Neural Network Inference Library Standard for Portable, Efficient Code” tutorial at the May 2018 Embedded Vision Summit. OpenVX is an industry-standard computer vision and neural network inference API designed for efficient implementation on a variety of embedded platforms. The API
Max Larin, CEO of XIMEA, presents the “High-end Multi-camera Technology, Applications and Examples” tutorial at the May 2018 Embedded Vision Summit. For OEMs and system integrators, many of today’s applications in VR/AR/MR, ADAS, measurement and automation require multiple coordinated high performance cameras. Current generic components are not optimized to achieve the desired traits in terms
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Gordon Hands, Director of Marketing for IP and Solutions at Lattice Semiconductor, presents the "Programmable CNN Acceleration in Under 1 Watt" tutorial at the May 2018 Embedded Vision Summit. Driven by factors such as privacy concerns, limited network bandwidth and the need for low latency, system designers are increasingly interested in implementing artificial intelligence (AI)
Greg Lytle, VP of Engineering at Au-Zone Technologies, presents the “Deploying CNN-based Vision Solutions on a $3 Microcontroller” tutorial at the May 2018 Embedded Vision Summit. In this presentation, Lytle explains how his company designed, trained and deployed a CNN-based embedded vision solution on a low-cost, Cortex-M-based microcontroller (MCU). He describes the steps taken to
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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