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HANDWRITTEN DIGIT RECOGNITION USING BACK PROPAGATION WORK& K-NEAREST NEIGHBOUR CLASSIFIER 基于反向传播神经网络和K-最近邻分类器的手写数字识别.pdf

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International Journal of Electrical, Electronics and Data Communication, ISSN (p): 2320-2084, Volume-1, Issue-, July-2013
HANDWRITTEN DIGIT RECOGNITION USING BACK
PROPAGATION NEURAL NETWORK& K-NEAREST NEIGHBOUR
CLASSIFIER

1RAHUL R. TIWARI, 2APARNAVISHWANATH, 3DHANASHREE WADHONE

Department of Electronics, Fr. Conceicao Rodrigues College of Engineering, Mumbai University
Fr. Agnel Ashram, Bandstand, Bandra (W), Mumbai
Email: ******@, ******@, dhanashree.******@

Abstract: Handwriting recognition has become one of the hottest directions in the field of image processing. It can very well
transform any handwritten content into a plain text file. This is being widely used in cheque recognition, mail sorting,
scanning documents, reading aid for the blind and so on. This paper attempts to recognize handwritten digits using
Backpropagation (BP) neural network and k-Nearest Neighbour Algorithm and then compare the results to suggest an
optimum classifier amongst the two of them.

Keywords- Handwriting recognition,

HANDWRITTEN DIGIT RECOGNITION USING BACK PROPAGATION WORK& K-NEAREST NEIGHBOUR CLASSIFIER 基于反向传播神经网络和K-最近邻分类器的手写数字识别来自淘豆网m.daumloan.com转载请标明出处.