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The goal of this thesis work is to implement a convolutional neural network on an FPGA device with the capability of recognising human sign language. The set of gestures that the neural network can identify has been taken from the Swedish sign language, and it consists of the signs used for representing the letters of the Swedish alphabet (a.k.a. fingerspelling). The motivation driving this projec
