Image processing based on supervised learning in neural networks

Akira Hasegawa; Wei Zhang; Kazuyoshi Itoh; Yoshiki Ichioka

doi:10.1117/12.50444

1 November 1991 Image processing based on supervised learning in neural networks

Akira Hasegawa, Wei Zhang, Kazuyoshi Itoh, Yoshiki Ichioka

Proceedings Volume 1621, Optical Memory and Neural Networks; (1991) https://doi.org/10.1117/12.50444
Event: Optical Memory and Neural Networks, 1991, Zvenigorod, Russian Federation

Abstract

We applied a learning network to the image processing of human cornea endothelial micrograms. Our neural model is a feed-forward network with interconnections between units constrained to be locally space-invariant to perform space-invariant processing. The network is trained by the error back propagation with some small parts of micrograms and their cell membrane images which are outline drawing made by hand. After training, the network showed good performance with unexpenenced micrograms. The final membrane images were obtained after additional processing by a conventional digital filter that is based on mathematical morphology and linear filtering.

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Akira Hasegawa, Wei Zhang, Kazuyoshi Itoh, and Yoshiki Ichioka "Image processing based on supervised learning in neural networks", Proc. SPIE 1621, Optical Memory and Neural Networks, (1 November 1991); https://doi.org/10.1117/12.50444

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KEYWORDS

Image processing

Neural networks

Cornea

Image filtering

Machine learning

Optical storage

Digital filtering

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