boosting 알고리즘의 개선을 위한 연구들

2. boosting 알고리즘의 개선을 위한 연구들

  - Real Adaboost 
[1] B. Wu, H. Ai, C. Huang, and S. Lao, "Fast Rotation Invariant Multi-View Face Detection Based on Real AdaBoost," Proc. IEEE Conf. Automatic Face and Gesture Recognition, pp.79-84, 2004.
[2] R. E. Schapire and Y. Singer, "Improved Boosting Algorithms Using Confidence-Rated Predictions," Machine Learning, Vol.37, pp.297-336, 1999.

 

- FloatBoost
[3] S. Z. Li and Z. Q. Zhang, "FloatBoost Learning and Statistical Face Detection," IEEE Trans.Pattern Analysis and Machine Intelligence, Vol.26, No.9, pp.1112-1123, 2004(9).

 

- KLBoosting
[4] C. Liu and H. Y. Shum, "Kullback-Leibler Boosting," Proc. Computer Vision and Pattern Recognition, pp.587-594, 2003.

 

- Tree Structured Cascade
[5] Chang Huang, Haizhou Ai, Yuan Li, and Shihong Lao, “Vector Boosting for Rotation Invariant Multi-view Face Detection,” International Conference on Computer Vision (ICCV), 2005.

 

- Gentle Adaboost
[6] Alexander Kuranov, Rainer Lienhart, and Vadim Pisarevsky. An Empirical Analysis of Boosting Algorithms for Rapid Objects With an Extended Set of Haar-like Features. Intel Technical Report MRL-TR-July 02-01, 2002.