Information Technology

Neural Networks, CMOS Sensors Kick Off VLSI Symposium

20 May 2016

Rapid progress in developing deep neural networks and the evolution of stacked CMOS imaging sensors have brought applications once considered impossible—such as real-time translation and self-driving vehicles—closer to reality. The integration of these technology trends are the subjects of two plenary presentations that kick off the 2016 Symposia on VLSI Technology & Circuits. The Symposia is a premiere international conference on semiconductor technology that defines the pace, progress and evolution of microelectronics, scheduled from June 13-17, 2016, in Honolulu, Hawaii.

The conference’s overall theme, “Inflections for a Smart Society,” is reflected in the opening plenary sessions entitled “Enabling Future Progress in Machine Learning, by Olivier Temam of Google, Inc. This will be followed by a presentation on “Accelerating the Sensing World Through Imaging Evolution,” by Tetsuo Nomoto, Sony Semiconductor Solutions Corporation’s Vice President and Senior General Manager.

In the first plenary session, Temam will discuss the significant role that deep neural network development will play in advancing the progress of future computer systems. Recent advances in machine learning, driven by rapid increases in computing performance, have made possible larger neural networks and training sets.  

The second plenary session details the evolution of CMOS imaging sensor (CIS) technology and the future prospect of a connected society with “anywhere, anytime, anything” sensing capabilities. CIS technology now dominates the market for digital still cameras, outperforming predecessor systems with lower power consumption, better signal-to-noise ratio, and higher frame rate through the use of back-illuminated architecture and column-parallel ADCs.

More information about the Symposia plenary sessions is available here.



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