September 25th webcast - How to build embedded vision systems with off-the-shelf components
Embedded vision continues to grow as a buzzword and a hot topic within the community. Within the machine vision market, embedded vision may refer to the use of embedded PCs or embedded computers. Outside of the factory, however, people are using commercial off-the-shelf components to build embedded vision systems in applications related to the Internet of Things. In a free webcast on September 25, Dr. Daniel Lau, Professor of Electrical and Computer Engineering at the University of Kentucky will describe the building of embedded vision applications with off-the-shelf computer-on-modules, and will describe the process and the additional components that are needed. He will also discuss the design challenges, the benefits of embedded vision, and some of the new and emerging applications that these systems can be deployed in.
Professor of Electrical and Computer Engineering
University of Kentucky
Dr. Lau received his B.Sc. degree (with highest distinction) in Electrical Engineering from Purdue University, West Lafayette, IN, in 1995 and the Ph.D. degree from the University of Delaware, Newark, in 1999. Today, he is a Professor of Electrical and Computer Engineering at the University of Kentucky, Lexington. Prior, he was a DSP Engineer at Aware, Inc., and an Image and Signal Processing Engineer at Lawrence Livermore National Laboratory. His research interests include 3-D imaging sensors, 3-D fingerprint scanning and identification, and multispectral color acquisition and display with funding from the Department of Defense, National Science Foundation, and the National Institutes of Health. Aside from his academic pursuits, Dr. Lau is also Chief Technology Officer for Seikowave Inc, a technology startup providing ruggedized scanning systems for the oil and gas services industry.
Watch on any mobile device – phone or tablet - or listen while you drive to work!