Papers › Deep Big Simple Neural Nets Excel on Handwritten Digit Recognition
Deep Big Simple Neural Nets Excel on Handwritten Digit Recognition
Dan Claudiu Ciresan, Ueli Meier, Luca Maria Gambardella, Juergen Schmidhuber
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.
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