In this section, let's discuss popular deep CNNs (for example, VGG-18/19, ResNet, and InceptionNet) used for image classification. The following screenshot shows single-crop accuracies (top-1 accuracy: how many times the correct label has the highest probability predicted by the CNN) of the most relevant entries submitted to the ImageNet challenge, from AlexNet (Krizhevsky et al., 2012), on the far left, to the best performing, Inception-v4 (Szegedy et al., 2016):
Also, we shall train a VGG-16 CNN with Keras to classify the cat images against the dog images.
