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.
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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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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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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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
Jeff Gehlhaar, Vice President of Technology, Corporate Research and Development, at Qualcomm, presents the "Deep-learning-based Visual Perception in Mobile and Embedded Devices: Opportunities and Challenges" tutorial at the May 2015 Embedded Vision Summit. Deep learning approaches have proven extremely effective for a range of perceptual tasks, including visual perception. Incorporating deep-learning-based visual perception into devices
Faris Alqadah, CEO and Co-Founder of QM Scientific, delivers the presentation "Combining Vision, Machine Learning and Natural Language Processing to Answer Everyday Questions" at the May 2015 Embedded Vision Alliance Member Meeting. Faris explains how his company's GPU-accelerated Quazi platform combines proprietary natural language processing, computer vision and machine learning technologies to extract, connect and
Mike Aldred, Electronics Lead at Dyson, presents the "Bringing Computer Vision to the Consumer" keynote at the May 2015 Embedded Vision Summit. While vision has been a research priority for decades, the results have often remained out of reach of the consumer. Huge strides have been made, but the final, and perhaps toughest, hurdle is
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Moshe Shahar, Director of System Architecture at CEVA, presents the "Evolution of Object Recognition in Embedded Systems" tutorial at the May 2015 Embedded Vision Summit. Camera-enabled devices have made great strides in performance and quality in recent years, but they still fall far short of human visual perception. To reach their potential, vision-enabled systems must
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Doug Johnston, Founder and Vice President of Technology at Prism Skylabs, delivers the presentation "Keeping Brick and Mortar Relevant: A Look Inside Prism Skylabs and Retail Analytics" at the December 2014 Embedded Vision Alliance Member Meeting. Doug explains how his firm is using vision to provide retailers with actionable intelligence based on consumer behavior.
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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