Application of the fuzzy Kohonen clustering network to remote-sensed data processing

Palma N. Blonda; A. Bennardo; Guido Pasquariello; Giuseppe Satalino; Vincenza la Forgia

doi:10.1117/12.243245

14 June 1996 Application of the fuzzy Kohonen clustering network to remote-sensed data processing

Palma N. Blonda, A. Bennardo, Guido Pasquariello, Giuseppe Satalino, Vincenza la Forgia

Proceedings Volume 2761, Applications of Fuzzy Logic Technology III; (1996) https://doi.org/10.1117/12.243245
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

In this work the effectiveness of the fuzzy Kohonen clustering network (FKCN) has been explored in two classification experiments of remote sensed data. The FKCN has been introduced in a multi-modular neural classification system for feature extraction before labeling. The unsupervised module is connected in cascade with the next supervised module, based on the backpropagation learning rule. The performance of the FKCN has been evaluated in comparison with those of a conventional Kohonen self organizing map (SOM) neural network. Experimental results have proved that the fuzzy clustering network can be used for complex data pre-processing.

Citation Download Citation

Palma N. Blonda, A. Bennardo, Guido Pasquariello, Giuseppe Satalino, and Vincenza la Forgia "Application of the fuzzy Kohonen clustering network to remote-sensed data processing", Proc. SPIE 2761, Applications of Fuzzy Logic Technology III, (14 June 1996); https://doi.org/10.1117/12.243245

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