Title :
A fuzzy neural network model (FNN model) for classification using Landsat-TM image data
Author :
Zhang, Lijian ; Hoshi, Takashi
Author_Institution :
Ibaraki Univ., Japan
Abstract :
A fuzzy backpropagation neural network model is proposed. In this model a fuzzy weighted distance (FWD) is used to interpret the degree of possibility of the input pattern belongs to a certain category in the fuzzy domain. An extended backpropagation (EBP) algorithm is employed to make the conventional multilayer perceptron (MLP) model can be used in fuzzy classification procedure. At the end, the Landsat-TM image data are used to inspect the effect of proposed model
Keywords :
backpropagation; fuzzy neural nets; geophysical signal processing; geophysical techniques; image classification; image colour analysis; multilayer perceptrons; optical information processing; remote sensing; FNN model; Landsat-TM; category; extended backpropagation algorithm; fuzzy backpropagation neural network model; fuzzy neural network model; fuzzy weighted distance; geophysical measurement technique; image classification; input pattern; land surface terrain mapping; multilayer perceptron; neural net; optical imaging; remote sensing; visible multispectral method; Artificial neural networks; Data engineering; Fuzzy neural networks; Fuzzy sets; Multi-layer neural network; Multilayer perceptrons; Neural networks; Pattern recognition; Remote sensing; Satellites;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1994. IGARSS '94. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation., International
Conference_Location :
Pasadena, CA
Print_ISBN :
0-7803-1497-2
DOI :
10.1109/IGARSS.1994.399456
