Image-processing 1,000 times faster is goal of new $5M contract. Loosely inspired by a biological brain's approach to making sense of visual information, a University of Michigan researcher is leading a project to build alternative computer hardware that could process images and video 1,000 times faster with 10,000 times less power than today's systems—all without sacrificing accuracy.
"With the proliferation of sensors, videos and images in today's world, we increasingly run into the problem of having much more data than we can process in a timely fashion," said Wei Lu, U-M associate professor of electrical engineering and computer science. "Our approach aims to change that. " Lu has been awarded an up-to-$5.7 million contract from the Defense Advanced Research Projects Agency to design and fabricate a computer chip based on so-called self-organizing, adaptive neural networks.
So far, Lu has received $1.3 million to begin work on the project. The new network will be designed to use a big-picture approach to image processing. Alicebot. 2010 IEEE International Conference on Robotics and A.