(Updated on July, 24th, 2017 with some improvements and Keras 2 style, but still a work in progress) CIFAR-10 is a small image (32 x 32) dataset made up of 60000 images subdivided into 10 main categories. Check the web page in the reference list in order to have further information about it and download the whole set. Considering our current screen resolutions, it’s not difficult saying that those images are no more than icons and indeed some of them are very hard to be classified even by human beings. Using Keras, I’ve modeled a deep convolutional network (VGGNet-like) in order to try a classification. I’m still investigating the best architecture (in CIFAR home page, there are very interesting references to papers and other results), however, I think it can be a good starting point. As the output is a softmax layer, it can also be interesting to evaluate mixed […]