Automatic target recognition using new support vector machine

  title={Automatic target recognition using new support vector machine},
  author={David Casasent and Yu-Chiang Wang},
  journal={Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.},
  pages={84-89 vol. 1}
A hierarchical classifier using a new SVRDM (support vector representation and discrimination machine) is proposed for automatic target recognition. An accuracy and distance-based method is used to design a hierarchical classifier. Our SVRDM hierarchical classifier has the ability to reject unseen non-object classes and clutter inputs. Uses of both iconic and spatial frequency domain features are considered. Initial recognition and rejection test results on infrared (IR) data are excellent. 


Publications referenced by this paper.
Showing 1-4 of 4 references

Casasent , " Face recognition and imposter rejection using a new SVRDM modified support vector machine

  • X. S. Zhou, T. S. Huang, C. Yuan, D.

Hierarchical multiclassification

  • M. Bruynooghe H. Blockeel, S. Dzeroski
  • Proc . First International Workshop on…

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