Bootstrapping (machine learning)
- Bootstrapping (machine learning)
In machine learning, bootstrapping is a general technique that iteratively trains and evaluates a classifier in order to improve its performance. In object detection, it is often used in conjunction with AdaBoost algorithm for efficient processing of large databases. [P. Viola and M. Jones. "Rapid object detection using a boosted cascadeof simple features". CVPR, 2001.]
References
External links
* [http://personal.ee.surrey.ac.uk/Personal/Z.Kalal/Publications/bmvc2008.pdf Weighted Sampling for Large-Scale Boosting] More on bootstrapping for object detection.
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