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A New ART Neural Networks for Remote Sensing Image Classification

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3611))

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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.

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Author information

Authors and Affiliations

  1. Information Engineering University, No. 306, P.O. BOX 1001, Zhengzhou, Henan, 450002, China

    AnFei Liu, BiCheng Li, Gang Chen & Xianfei Zhang

Authors
  1. AnFei Liu
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  2. BiCheng Li
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  3. Gang Chen
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  4. Xianfei Zhang
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Liu, A., Li, B., Chen, G., Zhang, X. (2005). A New ART Neural Networks for Remote Sensing Image Classification. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_6

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  • DOI: https://doi.org/10.1007/11539117_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28325-6

  • Online ISBN: 978-3-540-31858-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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