Article

Fused, multi-spectral automatic target recognition with XCS

Authors:

Avinahs Gandhe,

Ssu-Hsin Yu,

Raman Mehra,

Robert E. SmithAuthors Info & Claims

GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation

Page 1874

https://doi.org/10.1145/1276958.1277333

Published: 07 July 2007 Publication History

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Abstract

We present new results from our most recent efforts in applying XCS to automatic target recognition (ATR). We place particular emphasis on ATR as a series of linked problems, which include pre-processing of multi-spectral data, detection of objects (in this case, vehicles) in that data, and identification (classification) of those objects. Multi-spectral data contains visual imagery, and additional imagery from several infrared spectral bands. The performance of XCS, with robust features, notably exceeds that of a template-based classifier on the pre-processed multi-spectral data for vehicle identification.

References

[1]

Ravichandran, B., Gandhe, A. and Smith, R. E. (in press). Machine Learning for Robust Automatic Target Recognition. Information Fusion: The International Journal on Multi-Sensor, Multi-Source Information Fusion.

Google Scholar

[2]

Ravichandran, B., Gandhe, A., and Smith, R. E. (2005). XCS for Robust Automatic Target Recognition. In Proceedings of GECCO 2005. ACM Press.

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[3]

Gandhe, A., Yu, H.S., Mehra, R., Smith, R. E. (In Press). XCS for Fusing Multi-Spectral Data in Automatic Target Recognition in Bull, L., Bernado Mansilla, E., and Holmes, J. Learning Classifier Systems in Data Mining. Springer--Verlag.

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Cited By

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Siddique AIqbal MBrowne W(2016)A comprehensive strategy for mammogram image classification using learning classifier systems2016 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2016.7744060(2201-2208)Online publication date: Jul-2016
https://doi.org/10.1109/CEC.2016.7744060
Ebadi TZhang MBrowne WMoore J(2012)XCS-based versus UCS-based feature pattern classification systemProceedings of the 14th annual conference on Genetic and evolutionary computation10.1145/2330163.2330280(839-846)Online publication date: 7-Jul-2012
https://dl.acm.org/doi/10.1145/2330163.2330280
Lanzi P(2008)Learning classifier systems: then and nowEvolutionary Intelligence10.1007/s12065-007-0003-31:1(63-82)Online publication date: 8-Feb-2008
https://doi.org/10.1007/s12065-007-0003-3

Index Terms

Fused, multi-spectral automatic target recognition with XCS
1. Computing methodologies
  1. Machine learning

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Information & Contributors

Information

Published In

GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation

July 2007

2313 pages

ISBN:9781595936974

DOI:10.1145/1276958

General Chair:
Hod Lipson
Cornell University, USA

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 July 2007

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GECCO07

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GECCO07: Genetic and Evolutionary Computation Conference

July 7 - 11, 2007

London, England

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GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

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Siddique AIqbal MBrowne W(2016)A comprehensive strategy for mammogram image classification using learning classifier systems2016 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2016.7744060(2201-2208)Online publication date: Jul-2016
https://doi.org/10.1109/CEC.2016.7744060
Ebadi TZhang MBrowne WMoore J(2012)XCS-based versus UCS-based feature pattern classification systemProceedings of the 14th annual conference on Genetic and evolutionary computation10.1145/2330163.2330280(839-846)Online publication date: 7-Jul-2012
https://dl.acm.org/doi/10.1145/2330163.2330280
Lanzi P(2008)Learning classifier systems: then and nowEvolutionary Intelligence10.1007/s12065-007-0003-31:1(63-82)Online publication date: 8-Feb-2008
https://doi.org/10.1007/s12065-007-0003-3

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Context-aided false alarm reduction for SAR automatic target recognition

Target-Centered Models and Information-Theoretic Segmentation for Automatic Target Recognition

XCS for robust automatic target recognition