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Vehicle Detection Using a Hardware-Implemented Neural Net
January-February 1997 (vol. 12 no. 1)
pp. 15-21

The authors describe how they developed a vehicle-detection model based on a Radial Basis Function network and implemented it using the Ni1000 Recognition Accelerator, which can classify up to 32,000 patterns per second—several hundred times faster than the software approach to neural net processing. a detection system using this implementation had a success rate greater than 90%.

Citation:
Suryanarayana Mantri, Darcy Bullock, James Garrett, Jr., "Vehicle Detection Using a Hardware-Implemented Neural Net," IEEE Intelligent Systems, vol. 12, no. 1, pp. 15-21, Jan.-Feb. 1997, doi:10.1109/64.577408
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