[PDF][PDF] Comparison of learning algorithms for handwritten digit recognition
International conference on artificial neural networks, 1995•academia.edu
COMPARISON OF LEARNING ALGORITHMS FOR HANDWRITTEN DIGIT RECOGNITION
Page 1 COMPARISON OF LEARNING ALGORITHMS FOR HANDWRITTEN DIGIT
RECOGNITION Y. LeCun, L. Jackel, L. Bottou, A. Brunot, C. Cortes, J. Denker, H. Drucker, I.
Guyon, U. M uller, E. S ackinger, P. Simard, and V. Vapnik Bell Laboratories, Holmdel, NJ
07733, USA Email: yann@research.att.com Abstract This paper compares the performance
of several classi er algorithms on a standard database of handwritten digits. We consider …
Page 1 COMPARISON OF LEARNING ALGORITHMS FOR HANDWRITTEN DIGIT
RECOGNITION Y. LeCun, L. Jackel, L. Bottou, A. Brunot, C. Cortes, J. Denker, H. Drucker, I.
Guyon, U. M uller, E. S ackinger, P. Simard, and V. Vapnik Bell Laboratories, Holmdel, NJ
07733, USA Email: yann@research.att.com Abstract This paper compares the performance
of several classi er algorithms on a standard database of handwritten digits. We consider …
Abstract
This paper compares the performance of several classi er algorithms on a standard database of handwritten digits. We consider not only raw accuracy, but also rejection, training time, recognition time, and memory requirements.
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