14 June 1996 Real-time compact optoelectronic neural networks for face recognition
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We describe a nonlinear joint transform correlator-based two-layer neural network that uses a supervised learning algorithm for real-time face recognition. The system is trained with a sequence of facial images and is able to classify an input face image in real-time. Computer simulations and optical experimental results are presented. The processor can be manufactured into a compact low-cost optoelectronic system. The use of the nonlinear joint transform correlator provides good noise robustness and good image discrimination.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bahram Javidi, Bahram Javidi, Jian Li, Jian Li, } "Real-time compact optoelectronic neural networks for face recognition", Proc. SPIE 2749, Photonic Component Engineering and Applications, (14 June 1996); doi: 10.1117/12.243104; https://doi.org/10.1117/12.243104


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