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A Study on the Number Recognition using Cellular Neural Network  

전흥우 (금오공과대학 전자공학과)
김명관 (구미전자공고 전자기계과)
정금섭 (구미기능대학 생산자동화과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.6, no.6, 2002 , pp. 819-826 More about this Journal
Abstract
Cellular neural networks(CNN) are neural networks that have locally connected characteristics and real-time image processing. Locally connected characteristics are suitable for VLSI implementation. It also has applications in such areas as image processing and pattern recognition. In this thesis cellular neural networks are used for feature detection in number recognition at the stage of re-processing. The four or six directional shadow detectors are used in numbers recognition. At the stage of classification, this result of feature detection was simulated by using a multi-layer back Propagation neural network. The experiments indicate that the CNN feature detectors capture good features for number recognition tasks.
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