Introduction of convolution neural networks » Data Is Utopia

The history of Convolutional neural networks have a remote origin. It is actually in 1979, when Professor Kunihiko Fukushima proposed a hierarchical, multilayered artificial neural network called The neocognitron. The neocognitron has been used for solving the problem of handwritten character recognition and some other pattern recognition tasks, and served as the inspiration for convolutional neural networks. But, if you asked about the history of the neocognitron, we simply can tell you that it was inspired by the model proposed by Hubel & Wiesel in 1959. They found two types of cells in the visual primary cortex called simple cells and complex cells, and also proposed a cascading model of these two types of cells for use in pattern recognition tasks.