Embedded Vision Insights: February 18, 2016 Edition

Dear Colleague,

I'll begin this edition with a reminder: next Monday, February 22 from 9 AM to 5:30 PM in Santa Clara, California, the primary developers of the popular open-source Caffe convolutional neural network framework will present a one-day in-depth technical tutorial on deep learning for vision. See a recently published interview with these same developers for more information on Caffe, and register for the tutorial online without delay, while the few remaining spots are still available.

Here's another reminder: the deadline for entries for the Vision Tank, a deep learning- and vision-based product competition whose finalists will present at the Embedded Vision Summit, is March 1. Don't wait to begin brainstorming and registering; application submission information is available on the competition page. And while you're at it, also register for the Summit, an educational forum for product creators interested in incorporating visual intelligence into electronic systems and software, taking place in Santa Clara, California May 2-4. Receive a 15% Early Bird discount by using promotional code 07EVI.

While you're on the Alliance website, make sure to also check out the other great recently published content there. For example, a three-part series of technical articles from ARM covers accelerating the mixed-radix Fast Fourier Transform (FFT) on Mali GPUs using OpenCL; a related FFT tutorial is also new. Also newly published is the latest in a series of technical articles from Imagination Technologies, this one an introduction to implementing computer vision functions on PowerVR GPUs. There's also an article from CEVA on the relative pros and cons of hardware- versus software-based video stabilization, and a blog post from BDTI on deep learning for video analysis. And make sure to take a look at the multiple recent video demonstrations of embedded vision technologies and products from Alliance member companies, as well as numerous new-product press releases.

Thanks as always for your support of the Embedded Vision Alliance, and for your interest in and contributions to embedded vision technologies, products and applications. I welcome your suggestions on what the Alliance can do to better service your needs.

Brian Dipert
Editor-In-Chief, Embedded Vision Alliance

"Convolutional Networks: Unleashing the Potential of Machine Learning for Robust Perception Systems," a Presentation from Yann LeCun
Yann LeCun, Director of AI Research at Facebook and Silver Professor of Data Science, Computer Science, Neural Science, and Electrical Engineering at New York University, presents the "Convolutional Networks: Unleashing the Potential of Machine Learning for Robust Perception Systems" keynote at the May 2014 Embedded Vision Summit. Convolutional Networks (ConvNets) have become the dominant method for a wide array of computer perception tasks including object detection, object recognition, face recognition, image segmentation, visual navigation, handwriting recognition, as well as acoustic modeling for speech recognition and audio processing. They are a particular embodiment of the concept of "deep learning" in which all the layers in a multi-layer architecture are subject to training. This presentation demonstrates several practical applications of ConvNets, which are particularly easy to implement in hardware, particularly using dataflow architectures, and which bring the promise of real-time embedded systems capable of impressive image recognition tasks with applications to smart cameras, and mobile devices, automobiles, and robots.

Argus Insights Overview of Its Embedded Vision Market Analysis Capabilities
John Feland, CEO and Founder of Argus Insights, discusses the company's embedded vision activities at the December 2015 Embedded Vision Alliance Member Meeting. Specifically, Feland discusses how his company is able to track trends on social media related to embedded vision in general and the Embedded Vision Alliance in particular.

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