Convolutional Neural Networks - rugbyprof/5443-Data-Mining GitHub Wiki

CNNs, like neural networks, are made up of neurons with learnable weights and biases. Each neuron receives several inputs, takes a weighted sum over them, pass it through an activation function and responds with an output. The whole network has a loss function and all the tips and tricks that we developed for neural networks still apply on CNNs. CNN is a class of deep, feed-forward artificial neural networks that has successfully been applied to analyze visual imagery. Convolutional networks were inspired by biological processes in which the connectivity pattern between neurons is inspired by the organization of the animal visual cortex. ConvNets have been successful in identifying objects, traffic signs, and faces. It is also able to recognize scenes and the system is able to suggest relevant captions. They have applications in image and video recognition, recommender systems and natural language processing.