Title :
A new self-organizing method and its application to handwritten digit recognition
Author :
Shimada, Tsuyoshi ; Nishimura, Kazuo ; Haruki, Kazuhito
Author_Institution :
Toshiba Corp., Kanagawa, Japan
Abstract :
A self-organizing method for neural networks is proposed. This method reduces the calculation for learning considerably, and can be applied to real application problems, where many samples must be treated. The method has been applied to handwritten digit recognition. Samples incorrectly recognized have been reduced to 1/4 (learning data) or 2/3 (unknown data), compared with the multiple similarity method, which is a conventional statistical pattern classification method
Keywords :
character recognition; computerised pattern recognition; learning systems; neural nets; self-adjusting systems; handwritten digit recognition; learning; multiple similarity method; neural networks; self-organizing method; statistical pattern classification method; Application software; Character recognition; Handwriting recognition; Image recognition; Large-scale systems; Neural networks; Neurons; Pattern classification; Pattern recognition; Software engineering;
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
DOI :
10.1109/IJCNN.1991.155189
