In this paper, we show that learning features with convolutional neural networks is better than using hand-crafted features for handwritten word recognition. We consider two kinds of systems: a grapheme based segmentation and a sliding window segmen
The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a
