Convolutional neural network architecture for hand gesture recognition

This paper presents the design of a convolutional neural network architecture using the MatConvNet library for MATLAB in order to achieve the recognition of 2 classes of hand gestures: ”open” and ”closed”. Six architectures were implemented to which their hyperparameters and depth were varied to observe their behavior through the validation error in the training and accuracy in the estimation of each one of the set classes, which was evaluated by a matrix of confusion. Given each of these results, the neural network with the best performance was chosen.