Michael Tusch presents the "Video Cameras Without Video: Opportunities For Sensing With Embedded Vision" tutorial at the May 2017 Embedded Vision Summit. Within the next few years, network cameras will cease to be regarded primarily as image capture devices. They will instead transform into intelligent data capture nodes whose functionality will in many, but not […]
Tim Hartley, Senior Product Manager in the Imaging and Vision Group at ARM, presents the "Computer Vision on ARM: The Spirit Object Detection Accelerator" tutorial at the May 2017 Embedded Vision Summit. In 2016, ARM released Spirit, a dedicated object detection accelerator, bringing industry-leading levels of power- and area-efficiency to computer vision workflows. In this
On May 24, 2017 at 1PM ET (10AM PT), Xilinx will deliver a free hour-long webinar entitled "Caffe to Zynq: State-of-the-Art Machine Learning Inference Performance in Less Than 5 Watts", in partnership with the Embedded Vision Alliance Here's the description, from the event registration page: Machine learning research is advancing daily with new network architectures,
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 the Embedded Vision
Embedded Vision Insights: May 23, 2017 Edition Read More +
Vadim Pisarevsky, Software Engineering Manager at Intel, presents the "Making OpenCV Code Run Fast" tutorial at the May 2017 Embedded Vision Summit. OpenCV is the de facto standard framework for computer vision developers, with a 16+ year history, approximately one million lines of code, thousands of algorithms and tens of thousands of unit tests. While
“Making OpenCV Code Run Fast,” a Presentation from Intel Read More +
Most Innovative Vision-based Product Award Winners Selected at 2017 Embedded Vision Summit WALNUT CREEK, Calif., May 22, 2017, /PRNewswire/ — On May 2, 2017 at the 2017 Embedded Vision Summit, two innovative vision-based products received awards in the second annual Vision Tank start-up competition. The Judges' Award went to Lucid's LucidCam, a point-and-shoot virtual reality
Cormac Brick, Director of Machine Intelligence for Intel's Movidius Group, presents the "The Battle Between Traditional Algorithms and Deep Learning: The 3 Year Horizon" tutorial at the May 2017 Embedded Vision Summit. Deep learning techniques are gaining in popularity for many vision tasks. Will they soon dominate every facet of embedded vision? Cormac Brick from
SAN JOSE, Calif., May 18, 2017 /PRNewswire/ — Xilinx, Inc. (XLNX) today announced that it has invested in DeePhi Tech, a recognized leader in machine learning specializing in deep compression, compiling toolchain, and system-level optimization. Leveraging the architectural advantages of Xilinx® devices for machine learning, DeePhi provides inference platforms from edge to cloud for the
Xilinx Invests in Machine Learning Pioneer DeePhi Tech Read More +
This blog post was originally published at Imagination Technologies' website. It is reprinted here with the permission of Imagination Technologies. Having recently returned from another exciting Embedded Vision Summit show we’d like to share our thoughts in a blog post. This year’s event once again impressed, with compelling conversations and discussions about vision and surrounding
Embedded Vision Summit 2017: Thoughts From the Floor Read More +
Mario Bergeron, Technical Marketing Engineer at Avnet, demonstrates the company's latest embedded vision technologies and products at the May 2017 Embedded Vision Summit. Specifically, Bergeron explains how the Xilinx reVISION stack was used to target a sensor fusion algorithm on the Avnet PicoZed Embedded Vision Kit. Written entirely in C/C++, the image fusion algorithm was
Avnet Demonstration of Sensor Fusion Acceleration Using the Xilinx reVISION Stack Read More +
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