Dr. Takeo Kanade, U.A. and Helen Whitaker Professor at Carnegie Mellon University, presents the “Think Like an Amateur, Do As an Expert: Lessons from a Career in Computer Vision” tutorial at the May 2018 Embedded Vision Summit. In this keynote presentation, Dr. Kanade shares his experiences and lessons learned in developing a vast range of […]
Gian Marco Iodice, Senior Software Engineer in the Machine Learning Group at Arm, presents the “Even Faster CNNs: Exploring the New Class of Winograd Algorithms” tutorial at the May 2018 Embedded Vision Summit. Over the past decade, deep learning networks have revolutionized the task of classification and recognition in a broad area of applications. Deeper
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
“High-end Multi-camera Technology, Applications and Examples,” a Presentation from XIMEA Read More +
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