NDLI: An integrated neural concurrent system for pattern recognition: basic element

Content Provider	IEEE Xplore Digital Library
Author	Vassallo, G. Pilato, G. Sorbello, F.
Copyright Year	2003
Description	Author affiliation: Centre per la Ricerca Elettronica in Sicilia, Palermo, Italy (Vassallo, G.)
Abstract	The article outlines a methodology to automatically select a neural-based pattern classifier. A set of neural-based specialized pattern recognizers is generated, trained and successively it is automatically chosen, among them, one which has the "best" generalization capabilities according to a quality index, that does not require the use of any test set. Furthermore, it is illustrated the architecture of a basic element, based on the EaNet neural classifier, of a more complex framework that will be designed for concurrent pattern recognition in networked repositories of patterns. The effectiveness of the proposed approach has been tested as an example on the "NIST Special database 19" of handwritten characters images and it has also been verified using the traditional technique of the test set. For completeness, the methodology has been also tested using a traditional neural feed-forward classifier using sigmoids as activation function of its units belonging to the hidden layer. Experimental results show good performance of the proposed methodology.
Sponsorship	IEEE Instrumentation and Measurement Soc. IEEE Hungary Section
Starting Page	93
Ending Page	98
File Size	418825
Page Count	6
File Format	PDF
ISBN	0780378644
DOI	10.1109/ISP.2003.1275820
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-09-06
Publisher Place	Hungary
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data analysis Image databases Councils Mobile agents Neural networks Computer networks Pattern recognition Character recognition Feedforward systems Testing
Content Type	Text
Resource Type	Article

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