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» Boosting Object Detection Using Feature Selection
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ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 5 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu
ICRA
2009
IEEE
165views Robotics» more  ICRA 2009»
14 years 2 months ago
Robust servo-control for underwater robots using banks of visual filters
—We present an application of machine learning to the semi-automatic synthesis of robust servo-trackers for underwater robotics. In particular, we investigate an approach based o...
Junaed Sattar, Gregory Dudek
MCS
2007
Springer
14 years 1 months ago
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Joseph DePasquale, Robi Polikar
CVPR
2006
IEEE
14 years 9 months ago
Image-Based Multiclass Boosting and Echocardiographic View Classification
We tackle the problem of automatically classifying cardiac view for an echocardiographic sequence as a multiclass object detection. As a solution, we present an imagebased multicl...
Shaohua Kevin Zhou, J. H. Park, Bogdan Georgescu, ...
ICIP
2008
IEEE
14 years 9 months ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram