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K. Fukushima
ABSTRACT
A model of a neural network is presented that offers insight into the brain's complex mechanisms as well as design principles for information processors. The model has properties and abilities that most modern computers and pattern recognizers do not possess; pattern recognition, selective attention, segmentation, and associative recall. When a composite stimulus consisting of two or more patterns is presented, the model pays selective attention to each of the patterns one after the other, segments a pattern from the rest, and recognizes it separately in contrast to earlier models. This model has perfect associative recall, even for deformed patterns, without regard to their positions. It can be trained to recognize any set of patterns. 
ECVision indexed and annotated bibliography of cognitive computer vision publications
This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1
The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
A Neural Network for Visual Pattern RecognitionSite generated on Friday, 06 January 2006