A comparison study between MLP and convolutional neural network models for character recognition

Author:

Ben Driss S.1,Soua M.1,Kachouri R.1,Akil M.1

Affiliation:

1. ESIEE Paris, IGM, A3SI (France)

Publisher

SPIE

Reference31 articles.

1. X., Xu Z., An P., Liu Q., Lu Y. Advances on Digital Television and Wireless Multimedia Communications. Communications in Computer and Information Science, vol 331. Springer

2. Comparative study of caffe, neon, theano, and torch for deep learning;Bahrampour;ICLR,2016

3. G. J. Alred and C. T. Brusaw and W. E. Oliu, Handbook of Technical Writing, St. Martin’s, New York, 2015

4. CNN Based Common Approach to Handwritten Character Recognition of Multiple Scripts,Document Analysis and Recognition (ICDAR);Maitra,2015

5. F.Schwenker and al., Three learning phases for radial-basis-function networks, Pergamon., 2000

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