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» Boosting Object Detection Using Feature Selection
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ECCV
2006
Springer
16 years 7 months ago
Maximally Stable Local Description for Scale Selection
Scale and affine-invariant local features have shown excellent performance in image matching, object and texture recognition. This paper optimizes keypoint detection to achieve sta...
Cordelia Schmid, Gyuri Dorkó
ICPR
2006
IEEE
16 years 6 months ago
A Trainable Similarity Measure for Image Classification
In object recognition problems a two-stage system is usually adopted composed of a fast and simple detector and a more complex classifier. This paper studies a design of the secon...
Jana Novovicová, Pavel Paclík, Rober...
WAPCV
2004
Springer
15 years 10 months ago
Learning of Position-Invariant Object Representation Across Attention Shifts
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...
Muhua Li, James J. Clark
SIGIR
2009
ACM
15 years 11 months ago
Detecting spammers and content promoters in online video social networks
A number of online video social networks, out of which YouTube is the most popular, provides features that allow users to post a video as a response to a discussion topic. These f...
Fabrício Benevenuto, Tiago Rodrigues, Virg&...
139
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GECCO
2006
Springer
171views Optimization» more  GECCO 2006»
15 years 8 months ago
Evolving ensemble of classifiers in random subspace
Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the div...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...