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MDL-Based Genetic Programming for Object Detection

Yingqiang Lin, Bir Bhanu
CVPRW 2003 pp. 60
doi:10.1109/CVPRW.2003.10062 /cvprw/2003/lin2003cvprw-mdlbased/

Abstract

In this paper, genetic programming (GP) is applied to synthesize composite operators from primitive operators and primitive features for object detection. To improve the efficiency of GP, smart crossover, smart mutation and a public library are proposed to identify and keep the effective components of composite operators. To prevent code bloat and avoid severe restriction on the GP search, a MDL-based fitness function is designed to incorporate the size of composite operator into the fitness evaluation process. The experiments with real synthetic aperture radar (SAR) images show that compared to normal GP, GP algorithm proposed here finds effective composite operators more quickly.

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Cite

Text

Lin and Bhanu. "MDL-Based Genetic Programming for Object Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2003. doi:10.1109/CVPRW.2003.10062

Markdown

[Lin and Bhanu. "MDL-Based Genetic Programming for Object Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2003.](https://mlanthology.org/cvprw/2003/lin2003cvprw-mdlbased/) doi:10.1109/CVPRW.2003.10062

BibTeX

@inproceedings{lin2003cvprw-mdlbased,
  title     = {{MDL-Based Genetic Programming for Object Detection}},
  author    = {Lin, Yingqiang and Bhanu, Bir},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2003},
  pages     = {60},
  doi       = {10.1109/CVPRW.2003.10062},
  url       = {https://mlanthology.org/cvprw/2003/lin2003cvprw-mdlbased/}
}