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ICPR
2008
IEEE
13 years 10 months ago
Asymmetric Real Adaboost
A cost-sensitive extension of Real Adaboost denoted as asymmetric Real Adaboost(RAB) is proposed. The two main differences between Asymmetric RAB and the na¨ıve RAB are (1) a Ch...
Zhanjun Wang, Chi Fang, Xiaoqing Ding
ISBI
2008
IEEE
14 years 5 months ago
Reducing false positive responses in lung nodule detector system by asymmetric adaboost
We are developing a complex computer aided diagnosis (CAD) system to detect small pulmonary nodules from helical CT scans. Here we present a classifier to reduce the number of fal...
Martin Dolejsi, Jan Kybic, Stanislav Tuma, Michal ...
CVPR
2006
IEEE
14 years 6 months ago
Learning Boosted Asymmetric Classifiers for Object Detection
Object detection can be posted as those classification tasks where the rare positive patterns are to be distinguished from the enormous negative patterns. To avoid the danger of m...
Xinwen Hou, Cheng-Lin Liu, Tieniu Tan
NIPS
2001
13 years 5 months ago
Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade
This paper develops a new approach for extremely fast detection in domains where the distribution of positive and negative examples is highly skewed (e.g. face detection or databa...
Paul A. Viola, Michael J. Jones
ESANN
2006
13 years 5 months ago
Designing neural network committees by combining boosting ensembles
The use of modified Real Adaboost ensembles by applying weighted emphasis on erroneous and critical (near the classification boundary) has been shown to lead to improved designs, ...
Vanessa Gómez-Verdejo, Aníbal R. Fig...