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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Wenyi Zhao, Ph.D., Director of the Vision and Sensor Group at DAQRI, delivers the presentation, "Augmented Reality for Industrial Productivity," at the March 2016 Embedded Vision Alliance Member Meeting. Zhao discusses how his firm’s computer-vision-enabled augmented reality helmet is being used to dramatically improve productivity in industrial applications.
“Augmented Reality for Industrial Productivity,” a Presentation from DAQRI Read More +
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
Thanks to improvements in processors, image sensors, and algorithms, more and more of our devices now — for the first time — are gaining the ability to see and understand the world around them. In this talk from the June 2015 Augmented World Expo, Jeff Bier (Founder of the Embedded Vision Alliance) highlights the opportunities
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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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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