DocumentCode :
1171597
Title :
A neural network for visual pattern recognition
Author :
Fukushima, Kunihiko
Author_Institution :
NHK Sci. & Tech. Res. Lab., Tokyo, Japan
Volume :
21
Issue :
3
fYear :
1988
fDate :
3/1/1988 12:00:00 AM
Firstpage :
65
Lastpage :
75
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.<>
Keywords :
neural nets; pattern recognition; associative recall; deformed patterns; information processors; neural network; selective attention; visual pattern recognition; Biological neural networks; Brain modeling; Humans; Laboratories; Network synthesis; Neural networks; Neurophysiology; Pattern recognition; Physics; Psychology;
fLanguage :
English
Journal_Title :
Computer
Publisher :
ieee
ISSN :
0018-9162
Type :
jour
DOI :
10.1109/2.32
Filename :
32
Link To Document :
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