A neural network component in a texture classification system

The use of neural network components allows large systems to benefit from the learning and robustness of neural networks, without facing the difficulties inherent in scaling monolithic neural networks. At the interfaces to a neural network component, knowledge must be represented in vector form. This paper describes a hybrid system for image texture classification. At the interface of the neural network component, knowledge is encoded in long binary vectors