English

Deep Big Simple Neural Nets Excel on Handwritten Digit Recognition

Neural and Evolutionary Computing 2012-03-06 v1 Artificial Intelligence

Abstract

Good old on-line back-propagation for plain multi-layer perceptrons yields a very low 0.35% error rate on the famous 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, and graphics cards to greatly speed up learning.

Keywords

Cite

@article{arxiv.1003.0358,
  title  = {Deep Big Simple Neural Nets Excel on Handwritten Digit Recognition},
  author = {Dan Claudiu Ciresan and Ueli Meier and Luca Maria Gambardella and Juergen Schmidhuber},
  journal= {arXiv preprint arXiv:1003.0358},
  year   = {2012}
}

Comments

14 pages, 2 figures, 4 listings

R2 v1 2026-06-21T14:52:27.012Z