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» Boosting with Diverse Base Classifiers
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ISBI
2009
IEEE
15 years 4 months ago
A Classifier Ensemble Based on Performance Level Estimation
In this paper, we introduce a new classifier ensemble approach, applied to tissue segmentation in optical images of the uterine cervix. Ensemble methods combine the predictions o...
Wei Wang, Yaoyao Zhu, Xiaolei Huang, Daniel P. Lop...
COLING
2004
14 years 9 months ago
Word Translation Disambiguation Using Bilingual Bootstrapping
This paper proposes a new method for word translation disambiguation using a machine learning technique called `Bilingual Bootstrapping'. Bilingual Bootstrapping makes use of...
Hang Li, Cong Li
CVPR
2009
IEEE
15 years 1 months ago
Efficiently training a better visual detector with sparse eigenvectors
Face detection plays an important role in many vision applications. Since Viola and Jones [1] proposed the first real-time AdaBoost based object detection system, much effort has ...
Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhan...
CVPR
2007
IEEE
15 years 11 months ago
A boosting regression approach to medical anatomy detection
The state-of-the-art object detection algorithm learns a binary classifier to differentiate the foreground object from the background. Since the detection algorithm exhaustively s...
Shaohua Kevin Zhou, Jinghao Zhou, Dorin Comaniciu
KDD
2007
ACM
190views Data Mining» more  KDD 2007»
15 years 10 months ago
Model-shared subspace boosting for multi-label classification
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
Rong Yan, Jelena Tesic, John R. Smith