Image-processing 1,000 times faster is goal of new $5M contract

August 16, 2013

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 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 networks will be made of conventional and innovative components called memristors that perform both logic and . Memristors are resistors with memory— that regulate electric current based on the history of the stimuli applied to them.

Because of their multitasking abilities, researchers say they could enable platforms that can process a vast number of signals in parallel and are capable of advanced machine learning. Systems that utilize them could be much more efficient than conventional computers in handling "big data" tasks such as analyzing images and video.

The new network will be designed to use a big-picture approach to . Rather than painstakingly rendering pixel by pixel, as today's computers do, the system would look at a whole image at once and identify deep structures in it through a process called inference.

"The idea is to recognize that most data in images or videos are essentially noise," Lu said. "Instead of processing all of it or transmitting it fully and wasting precious bandwidth, adaptive neural networks can extract key features and reconstruct the images with a much smaller amount of data."

Lu's ultimate goal in this project is to build a network that uses the memristors as, essentially, artificial synapses between conventional circuits, which could be considered artificial neurons. The synapses in a biological brain are the gaps between neurons across which neurons send chemical or electrical signals.

In a simpler, alternate version of the new network, Lu plans to build a system that uses memristors as memory nodes along traditional wired connections between circuits (rather than using the memristors as the connections themselves) to improve the efficiency of the machine's learning process.

After the systems are built, the researchers will train them to recognize common image features. They'll load them with thousands of images—cars in a busy street, aerial images and handwritten characters, for example.

During training, the connections from the input images to the artificial neurons will evolve spontaneously, Lu said, and afterwards each neuron should be able to identify one particular feature or shape. Then, when presented with a similar feature in a fresh image, only the neurons that find their assigned pattern or shape would fire and transmit information.

Explore further: Memristor chip could lead to faster, cheaper computers

Related Stories

Memristor chip could lead to faster, cheaper computers

March 17, 2009

( -- The memristor is a computer component that offers both memory and logic functions in one simple package. It has the potential to transform the semiconductor industry, enabling smaller, faster, cheaper chips ...

Cat brain: A step toward the electronic equivalent

April 14, 2010

A cat can recognize a face faster and more efficiently than a supercomputer. That's one reason a feline brain is the model for a biologically-inspired computer project involving the University of Michigan.

Recommended for you

Netherlands bank customers can get vocal on payments

August 1, 2015

Are some people fed up with remembering and using passwords and PINs to make it though the day? Those who have had enough would prefer to do without them. For mobile tasks that involve banking, though, it is obvious that ...

Power grid forecasting tool reduces costly errors

July 30, 2015

Accurately forecasting future electricity needs is tricky, with sudden weather changes and other variables impacting projections minute by minute. Errors can have grave repercussions, from blackouts to high market costs. ...

Microsoft describes hard-to-mimic authentication gesture

August 1, 2015

Photos. Messages. Bank account codes. And so much more—sit on a person's mobile device, and the question is, how to secure them without having to depend on lengthy password codes of letters and numbers. Vendors promoting ...


Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.