Extraction of Feature Attentive Regions in a Learnt Neural Network

Hideki SANO  Atsuhiro NADA  Yuji IWAHORI  Naohiro ISHII  

IEICE TRANSACTIONS on Information and Systems   Vol.E77-D   No.4   pp.482-489
Publication Date: 1994/04/25
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Neurocomputing)
Category: Image Processing
neural network,  degree of dependence,  pattern classification,  

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This paper proposes a new method of extracting feature attentive regions in a learnt multi-layer neural network. We difine a function which calculates the degree of dependence of an output unit on an inpur unit. The value of this function can be used to investigate whether a learnt network detects the feature regions in the training patterns. Three computer simulations are presented: (1) investigation of the basic characteristic of this function; (2) application of our method to a simpie pattern classification task; (3) application of our method to a large scale pattern classfication task.