Object Identification

“Designing Vision Systems for Human Operators and Workflows,” a Presentation from 8tree

Arun Chhabra of 8tree delivers the presentation "Designing Vision Systems for Human Operators and Workflows" at the February 2017 Embedded Vision Alliance Member Meeting. Chhabra explains how his company is deploying computer vision to enhance existing workflows in industries such as aircraft maintenance.

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“Intelligent Video Surveillance: Are We There Yet?,” a Presentation from CheckVideo

Nik Gagvani, President and General Manager of CheckVideo, delivers the presentation "Intelligent Video Surveillance: Are We There Yet?" at the September 2016 Embedded Vision Alliance Member Meeting. Gagvani provides an insider's perspective on vision-enabled video surveillance applications.

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“Using Vision to Enable Autonomous Land, Sea and Air Vehicles,” a Keynote Presentation from NASA JPL

Larry Matthies, senior research scientist at the NASA Jet Propulsion Laboratory, presents the "Using Vision to Enable Autonomous Land, Sea and Air Vehicles" keynote at the May 2016 Embedded Vision Summit. Say you’re an autonomous rover and you’ve just landed on Mars. Vexing questions now confront you: “Where am I and how am I moving?”

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Vision Processing Opportunities in Drones

UAVs (unmanned aerial vehicles), commonly known as drones, are a rapidly growing market and increasingly leverage embedded vision technology for digital video stabilization, autonomous navigation, and terrain analysis, among other functions. This article reviews drone market sizes and trends, and then discusses embedded vision technology applications in drones, such as image quality optimization, autonomous navigation,

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May 2016 Embedded Vision Summit Proceedings

The Embedded Vision Summit was held on May 2-4, 2016 in Santa Clara, California, as a educational forum for product creators interested in incorporating visual intelligence into electronic systems and software. The presentations presented at the Summit are listed below. All of the slides from these presentations are included in… May 2016 Embedded Vision Summit

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“Techniques for Efficient Implementation of Deep Neural Networks,” a Presentation from Stanford

Song Han, graduate student at Stanford, delivers the presentation "Techniques for Efficient Implementation of Deep Neural Networks" at the March 2016 Embedded Vision Alliance Member Meeting. Song presents recent findings on techniques for the efficient implementation of deep neural networks.

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Deep Learning Use Cases for Computer Vision (Download)

Six Deep Learning-Enabled Vision Applications in Digital Media, Healthcare, Agriculture, Retail, Manufacturing, and Other Industries The enterprise applications for deep learning have only scratched the surface of their potential applicability and use cases.  Because it is data agnostic, deep learning is poised to be used in almost every enterprise vertical… Deep Learning Use Cases for

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“Assistive Technology for the Visually Impaired,” a Presentation from UC Santa Cruz

Professor Roberto Manduchi of U.C. Santa Cruz delivers the presentation, "Assistive Technology for the Visually Impaired," at the December 2015 Embedded Vision Alliance Member Meeting. Professor Manduchi explores how embedded vision is being used to assist visually impaired individuals.

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Using Convolutional Neural Networks for Image Recognition

This article was originally published at Cadence's website. It is reprinted here with the permission of Cadence. Convolutional neural networks (CNNs) are widely used in pattern- and image-recognition problems as they have a number of advantages compared to other techniques. This white paper covers the basics of CNNs including a description of the various layers

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“Harman’s Augmented Navigation Platform—The Convergence of ADAS and Navigation,” a Presentation from Harman

Alon Atsmon, Vice President of Technology Strategy at Harman International, presents the "Harman’s Augmented Navigation Platform—The Convergence of ADAS and Navigation" tutorial at the May 2015 Embedded Vision Summit. Until recently, advanced driver assistance systems (ADAS) and in-car navigation systems have evolved as separate standalone systems. Today, however, the combination of available embedded computing power

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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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