Åge J. Eide

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The problem of facial recognition from grey-scale video images is approached using a two-stage neural network implemented in software. The first net finds the eyes of a person and the second neural network uses an image of the area around the eyes to identify the person. In a second approach the first network is implemented in hardware using the IBM ZISC036(More)
This research reports on a system able to classify di€erent signals containing auditive information based on capture of small signal segments present in speci®c types of sound. After using a Haar wavelet transform at the preprocessing stage, a neural network known as the O-algorithm compares segments from candidate audio signals against prede®ned templates(More)
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