Deep Learning with Modern Java Code

nice Java code with DeepNetts,
DeepNeetts with two dependencies only,
the data augmentation for variation generation,
DeepNetts supports all formats from java image IO,
max pool layer reduces the dimension of a problem,
convolutional layer is about pattern recognition,
convolutional layer slides a square shape over an image to recognise a pattern,
max pool layer is about downsizing,
the output layers is uses a mathematical soft max function,
output layer provides the prediction,
DeepNetts does not rely on the existence of GPU,