NDLI: A new scheme which incrementally generates neural networks for distorted handprinted Kanji pattern recognition

Content Provider	IEEE Xplore Digital Library
Author	kimura, Y.
Copyright Year	1994
Description	Author affiliation: NTT Human Interface Labs., Kanagawa, Japan (kimura, Y.)
Abstract	We present a recognition system that incrementally generates neural networks to solve the problem of error caused by sample distribution overlap among categories. The first stage neural network performs the easiest task which is to separate mostly nonoverlapping distributions, and leaves the difficult tasks such as separating overlapped distributions to the neural network(s) generated in the following stage(s). The new system improves its performance by assigning tasks to neural networks according to the degree of task difficulty and forms a specialized neural network. The new system achieves higher performance for the recognition of distorted Kanji patterns than the traditional neural networks which consist of only one neural network. The ability of the system to eliminate overlapped distributions is confirmed by analyzing the output distribution of the hidden units.
Starting Page	3852
Ending Page	3855
File Size	292877
Page Count	4
File Format	PDF
ISBN	078031901X
DOI	10.1109/ICNN.1994.374825
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-06-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Pattern recognition Nonlinear distortion Principal component analysis Error correction Humans Laboratories Telegraphy Telephony Degradation
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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