Edge AI and Vision Alliance

LETTER FROM THE EDITOR Dear Colleague, In the coming months, Embedded Vision Alliance member companies VeriSilicon and Xilinx will deliver several free, hour-long webinars on various computer vision topics, in partnership with the Alliance. On October 19 at 10 am Pacific Time, VeriSilicon will present "Learning at the Speed of Sight," which discusses how the

LETTER FROM THE EDITOR Dear Colleague, Next Thursday, September 22 from 9 am to 5 pm, the primary Caffe developers from U.C. Berkeley's Vision and Learning Center will present "Deep Learning for Vision Using CNNs and Caffe," a full-day detailed technical tutorial focused on convolutional neural networks (CNNs) for vision and the Caffe framework for

FEATURED VIDEOS "Tailoring Convolutional Neural Networks for Low-Cost, Low-Power Implementation," a Presentation from Synopsys Deep learning-based object detection using convolutional neural networks (CNN) has recently emerged as one of the leading approaches for achieving state-of-the-art detection accuracy for a wide range of object classes. Most of the current CNN-based detection algorithm implementations run on high-performance

FEATURED VIDEOS "3D from 2D: Theory, Implementation, and Applications of Structure from Motion," a Presentation from videantis Structure from motion uses a unique combination of algorithms that extract depth information using a single 2D moving camera. Using a calibrated camera, feature detection, and feature tracking, the algorithms calculate an accurate camera pose and a 3D

FEATURED VIDEOS Combining Flexibility and Low-Power in Embedded Vision Subsystems: An Application to Pedestrian Detection Bruno Lavigueur, Embedded Vision Subsystem Project Leader at Synopsys, presents a case study of a pedestrian detection application. Starting from a high-level functional description in OpenCV, he decomposes and maps the application onto a heterogeneous platform consisting of a high-performance