NOTE: This tutorial only works with 64-bit versions of EBLearn, as the dataset used is larger than 4GB when uncompressed.



In this tutorial, you will learn how to design, train and test a state-of-the-art classifier for the Stanford/Google Street View House Numbers dataset.

The model is based on Convolutional Networks (ConvNets) which learn all features from scratch rather than using hand-designed features.

More details can be found in the ICPR'12 and Arxiv papers.



