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» Discriminative Learning of Max-Sum Classifiers
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HICSS
2006
IEEE
163views Biometrics» more  HICSS 2006»
14 years 3 months ago
Learning Ranking vs. Modeling Relevance
The classical (ad hoc) document retrieval problem has been traditionally approached through ranking according to heuristically developed functions (such as tf.idf or bm25) or gene...
Dmitri Roussinov, Weiguo Fan
ECCV
2008
Springer
14 years 11 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
MLDM
2007
Springer
14 years 4 months ago
Ensemble-based Feature Selection Criteria
Recursive Feature Elimination (RFE) combined with feature ranking is an effective technique for eliminating irrelevant features when the feature dimension is large, but it is diffi...
Terry Windeatt, Matthew Prior, Niv Effron, Nathan ...
ICCV
2009
IEEE
15 years 2 months ago
Multiple Kernels for Object Detection
Our objective is to obtain a state-of-the art object category detector by employing a state-of-the-art image classifier to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...
CVPR
2009
IEEE
1119views Computer Vision» more  CVPR 2009»
15 years 5 months ago
Adaptive Contour Features in Oriented Granular Space for Human Detection and Segmentation
In this paper, a novel feature named Adaptive Contour Feature (ACF) is proposed for human detection and segmentation. This feature consists of a chain of a number of granules in...
Wei Gao (Tsinghua University), Haizhou Ai (Tsinghu...