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» Boosting with Diverse Base Classifiers
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ECCV
2008
Springer
16 years 3 months ago
Multiple Component Learning for Object Detection
Abstract. Object detection is one of the key problems in computer vision. In the last decade, discriminative learning approaches have proven effective in detecting rigid objects, a...
Boris Babenko, Pietro Perona, Piotr Dollár,...
WWW
2008
ACM
16 years 2 months ago
Floatcascade learning for fast imbalanced web mining
This paper is concerned with the problem of Imbalanced Classification (IC) in web mining, which often arises on the web due to the "Matthew Effect". As web IC applicatio...
Xiaoxun Zhang, Xueying Wang, Honglei Guo, Zhili Gu...
ICPR
2004
IEEE
16 years 2 months ago
Optimizing Nearest Neighbour in Random Subspaces using a Multi-Objective Genetic Algorithm
In this work, the authors have evaluated almost 20 millions ensembles of classifiers generated by several methods. Trying to optimize those ensembles based on the nearest neighbou...
Guillaume Tremblay, Robert Sabourin, Patrick Maupi...
WWW
2009
ACM
16 years 2 months ago
Combining anchor text categorization and graph analysis for paid link detection
In order to artificially boost the rank of commercial pages in search engine results, search engine optimizers pay for links to these pages on other websites. Identifying paid lin...
Kirill Nikolaev, Ekaterina Zudina, Andrey Gorshkov
AAAI
2008
15 years 4 months ago
Multimodal People Detection and Tracking in Crowded Scenes
This paper presents a novel people detection and tracking method based on a multi-modal sensor fusion approach that utilizes 2D laser range and camera data. The data points in the...
Luciano Spinello, Rudolph Triebel, Roland Siegwart