Читать книгу Machine Learning for Tomographic Imaging - Professor Ge Wang - Страница 59

The convolution neural network (CNN) is a popular kind of artificial neural network, which recently became a research focus in the fields of speech analysis and image recognition. In the HVS, there exist several information processing stages, from the V1 area, where simple cells have selective responses for directional structures, to the V4 area, where complex curvatures are identified. In the layer-by-layer process, the receptive field is gradually enlarged, and the image characteristics to which the neurons respond become more and more complicated. Inspired by the HVS, when an image is processed, the activities in the artificial neural network are made similar to those in the HVS. The CNN provides an excellent model for this mechanism of the HVS. That is to say, the convolution neural network extracts features layer by layer. The deeper the layer in the network, the more complex and higher dimensional the feature maps are.