NDLI: Efficient image classification using neural networks and multiresolution analysis

Content Provider	IEEE Xplore Digital Library
Author	Tirakis, A. Kollias, S.
Copyright Year	1993
Description	Author affiliation: Dept. Electr. Eng., Nat. Tech. Univ. of Athens, Greece (Tirakis, A.; Kollias, S.)
Abstract	The authors investigate a new efficient image classification strategy. They propose a multiresolution analysis of the images to be classified and use of feedforward neural networks to classify the images at various lower resolutions. This approach results in a major reduction of the networks' interconnection weights as well as the required learning times. The proposed approach is applied first to the images of the lowest resolution; if the classification results are not acceptable, it is successively repeated to the next images of higher resolution. A neural network architecture which incorporates most of the interconnection weights already computed at the lower level (i.e., the knowledge already acquired by the network of the previous resolution level) is proposed for this purpose. Experimental results illustrate the efficiency of the proposed multiresolution classification procedure in a real life application.<>
Starting Page	641
Ending Page	644
File Size	338200
Page Count	4
File Format	PDF
ISBN	0780374029
ISSN	15206149
DOI	10.1109/ICASSP.1993.319200
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1993-04-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image classification Neural networks Multiresolution analysis Image resolution Multi-layer neural network Finite impulse response filter Signal resolution Feature extraction Image recognition Image analysis
Content Type	Text
Resource Type	Article

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