LETTER FROM THE EDITOR Dear Colleague, Are you an early-stage start-up company developing a new product or service incorporating or enabling computer vision? Do you want to raise awareness of your company and products with vision industry experts, investors and entrepreneurs? Want a chance to win $5,000 in cash plus membership in the Embedded Vision […]
Embedded Vision Insights: December 19, 2017 Edition Read More +
This blog post was originally published at Alliance partner organization Khronos' website. It is reprinted here with the permission of the Khronos Group. There is a wide range of open-source deep learning training networks available today offering researchers and designers plenty of choice when they are setting up their project. Caffe, Tensorflow, Chainer, Theano, Caffe2,
Machine Learning’s Fragmentation Problem — and the Solution from Khronos Read More +
LETTER FROM THE EDITOR Dear Colleague, The Embedded Vision Summit is the preeminent conference on practical computer vision, covering applications at the edge and in the cloud. It attracts a global audience of over one thousand product creators, entrepreneurs and business decision-makers who are creating and using computer vision technology. The Embedded Vision Summit has
Embedded Vision Insights: December 5, 2017 Edition Read More +
Dr. Patrick Courtney, MBA, of tec-connection and the Standards in Laboratory Automation (SiLA) Consortium delivers the presentation "The Reverse Factory: Embedded Vision in High-Volume Laboratory Applications" at the Embedded Vision Alliance's September 2017 Vision Industry and Technology Forum. In his presentation, Courtney covers the following topics: Motivation: the need and the market Big applications today:
Dr. Anja Dieckmann of GfK Verein and Markus Iwanczok of GfK SE deliver the presentation "Using Vision to Collect Rich Data in the Moment of Truth for Retail Analytics and Market Research" at the Embedded Vision Alliance's September 2017 Vision Industry and Technology Forum. In their presentation, Dieckmann and Iwanczok cover the following topics: Market
Dr. Wojciech Samek of the Fraunhofer Heinrich Hertz Institute delivers the presentation "Methods for Understanding How Deep Neural Networks Work" at the Embedded Vision Alliance's September 2017 Vision Industry and Technology Forum. In his presentation, Dr. Samek covers the following topics: Unbeatable AI systems Deep neural network overview Opening the "black box" Summary
LETTER FROM THE EDITOR Dear Colleague, Google will deliver the free webinar "An Introduction to Developing Vision Applications Using Deep Learning and Google's TensorFlow Framework" on January 17, 2018 at 9 am Pacific Time, in partnership with the Embedded Vision Alliance. The webinar will be presented by Pete Warden, research engineer and technology lead on
Embedded Vision Insights: November 21, 2017 Edition Read More +
Charles Nespoulous of Chouette delivers the presentation "Using Drones with Embedded Vision to Safeguard Vineyard Health" at the Embedded Vision Alliance's September 2017 Vision Industry and Technology Forum. In his presentation, Nespoulous covers the following topics: Viticulture challenges The precision viticulture solution Chouette overview Implementation challenges Chouette's implementation approach Business model Future challenges
Dr. Christian Perwass of Bosch delivers the presentation "Introduction to Light Field Imaging" at the Embedded Vision Alliance's September 2017 Vision Industry and Technology Forum. In his presentation, Dr. Perwass discusses light field imaging's uniqueness, applicability, and implementation challenges and solutions.
“Introduction to Light Field Imaging,” a Presentation from Bosch Read More +
Auro Tripathy, Founding Principal at ShatterLine Labs, presents the "How CNNs Localize Objects with Increasing Precision and Speed" tutorial at the May 2017 Embedded Vision Summit. Locating objects in images (“detection”) quickly and efficiently enables object tracking and counting applications on embedded visual sensors (fixed and mobile). By 2012, progress on techniques for detecting objects
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