DocumentCode :
324550
Title :
Neocognitron with improved bend-extractors
Author :
Fukushima, Kunihiko ; Kimura, Eiji ; Shouno, Hayaru
Author_Institution :
Graduate Sch. of Eng. Sci., Osaka Univ., Japan
Volume :
2
fYear :
1998
fDate :
4-9 May 1998
Firstpage :
1172
Abstract :
We (1988) have reported previously that the performance of a neocognitron can be improved by a built-in bend-extracting layer. The conventional bend-extracting layer can detect bend points and end points of lines correctly, but not always crossing points of lines. This paper discusses that an introduction of a mechanism of disinhibition can make the bend-extracting layer detect not only bend points and end points but also crossing points of lines correctly. A neocognitron with this improved bend-extracting layer can recognize handwritten digits in the real world with a recognition rate of 98%
Keywords :
character recognition; edge detection; feature extraction; feedforward neural nets; bend points; bend-extracting layer; crossing points; end points; feature extraction; handwritten digit recognition; line detection; multilayer neural networks; neocognitron; Data mining; Handwriting recognition; Pattern recognition; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
ISSN :
1098-7576
Print_ISBN :
0-7803-4859-1
Type :
conf
DOI :
10.1109/IJCNN.1998.685939
Filename :
685939
Link To Document :
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