Fuzzy logic and neural techniques integration: An application to remotely sensed data

The paper reviews the most recent proposals on the integration of fuzzy and neural networks techniques. First, it focuses on the strategies developed and employed for the fuzzification of neural network architectures. Then it applies an unsupervised fuzzy architecture to the analysis of remotely sensed data and compares the results with those obtained by means of a conventional neural model.