This paper describes the application of neural networks to targets classification from multi-polarization ENVISAT-ASAR imagery. The used neural network is multilayer perception (MLP) with fast learning (FL), which is fully interconnected network. Accordingly, the training data sets may be taken from a known truth data in the ground. And finally, the results of proposed method are compared with that of the other classification ones, the in situ test data are from Zhaoqing in Guangdong Province of China
['Feiya Zhu', 'Huadong Guo', 'Qing Dong', 'Changlin Wang']
Multilayer perceptron classification for ENVISAT-ASAR imagery