Demystifying Deep Neural Networks

Monday, May 1, 10:45 AM - 11:45 AM
Summit Track: 

What are deep neural networks, and how do they work? In this talk, we provide an introduction to deep convolutional neural networks (CNNs), which have recently demonstrated impressive success on a wide range of vision tasks. Without using a lot of complex math, we introduce the basics of CNNs. We explore the differences between shallow and deep networks, and explain why deep learning has only recently become prevalent. We examine the different types of layers used in contemporary CNN designs and illustrate why networks composed of these layers are well suited to vision tasks.


Shehrzad Qureshi

Senior Engineer, BDTI

Shehrzad Qureshi is a Senior Engineer with BDTI. He has worked in a variety of computer vision and signal processing technologies and is the author of the book Embedded Image Processing on the TMS320C6000 DSP (Springer, 2005). He has an M.S. in Computer Engineering from Santa Clara University, and a B.S. in Computer Science from the University of California, Davis. He is an inventor or co-inventor on 7 U.S. issued patents, with more pending.

Earlier in his career, Shehrzad was Director of Software Engineering at Restoration Robotics. His 2009 computer vision patent was the first issuance for that company. Prior to Restoration Robotics, Shehrzad was the Software Manager at Biotech startup Labcyte Inc. Shehrzad has held individual contributor positions at Accuray Oncology, where he worked in medical imaging and Applied Signal Technology, where he worked on classified SIGINT defense programs.

Join us May 22-24, 2018 in Santa Clara, California.
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