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Deep convolutional neural networks are great at learning structures in signals and sequential data. Their performance have surpassed most non-convolutional algorithms on classical problems within the field of image analysis. A reason behind their success is that even though these networks generally need a great amount of examples to learn from, they can be used to learn smaller tasks through diffe
