ML Anthology

Bagging in Computer Vision

Bruce A. Draper, Kyungim Baek
CVPR 1998 pp. 144-149
doi:10.1109/CVPR.1998.698601 /cvpr/1998/draper1998cvpr-bagging/

Abstract

Previous research has shown that aggregated predictors improve the performance of non-parametric function approximation techniques. This paper presents the results of applying aggregated predictors to a computer vision problem, and shows that the method of bagging significantly improves performance. In fact, the results are better than those previously reported on other domains. This paper explains this performance in terms of the variance and bias.

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Cite

Text

Draper and Baek. "Bagging in Computer Vision." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998. doi:10.1109/CVPR.1998.698601

Markdown

[Draper and Baek. "Bagging in Computer Vision." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998.](https://mlanthology.org/cvpr/1998/draper1998cvpr-bagging/) doi:10.1109/CVPR.1998.698601

BibTeX

@inproceedings{draper1998cvpr-bagging,
  title     = {{Bagging in Computer Vision}},
  author    = {Draper, Bruce A. and Baek, Kyungim},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1998},
  pages     = {144-149},
  doi       = {10.1109/CVPR.1998.698601},
  url       = {https://mlanthology.org/cvpr/1998/draper1998cvpr-bagging/}
}