A new ART neural networks for remote sensing image classification

Authors:
AnFei Liu;BiCheng Li;Gang Chen;Xianfei Zhang
Affiliations:
Information Engineering University, Zhengzhou, Henan, China;Information Engineering University, Zhengzhou, Henan, China;Information Engineering University, Zhengzhou, Henan, China;Information Engineering University, Zhengzhou, Henan, China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Year:
2005

Citing 1
Cited 1

Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system

Neural Networks

An unsupervised method of classifying remotely sensed images using Kohonen self-organizing maps and agglomerative hierarchical clustering methods

International Journal of Remote Sensing

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Abstract

A new ART2A-C algorithm based on fuzzy operators to cluster the remote sensing images and aerials is proposed in this paper. By combining two ART ANNs with higher performance, the traditional ART2A-C is developed with the fuzzy operators introduced in matching rule. Then the proposed method is applied to the classification and the new network is implemented as well as two other existed ARTs respectively. Experimental results show that the new method outperforms the traditional ones.