Deep, big, simple neural nets for handwritten digit recognition

Neural Comput. 2010 Dec;22(12):3207-20. doi: 10.1162/NECO_a_00052. Epub 2010 Sep 21.

Abstract

Good old online backpropagation for plain multilayer perceptrons yields a very low 0.35% error rate on the MNIST handwritten digits benchmark. All we need to achieve this best result so far are many hidden layers, many neurons per layer, numerous deformed training images to avoid overfitting, and graphics cards to greatly speed up learning.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Artificial Intelligence*
  • Handwriting*
  • Pattern Recognition, Automated / methods*