Convolutional networks
CNNs are feed-forward networks modeled after the visual cortex found in animals. The visual cortex is arranged with overlapping neurons, and so in this type of network, the neurons are also arranged in overlapping sections, known as receptive fields. Due to their design model, they function with minimal preprocessing or prior knowledge, and this lack of human intervention makes them especially useful.
This type of network is used frequently in image and video recognition applications. They can be used for classification, clustering, and object recognition. CNNs can also be applied to text analysis by implementing Optical Character Recognition (OCR). CNNs have been a driving force in the machine learning movement in part due to their wide applicability in practical situations.
We are going to demonstrate a CNN using DL4J. The process will closely mirror the process we used in the Building an autoencoder in DL4J section. We will again use the Mnist dataset. This dataset...
