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» Combinations of Weak Classifiers
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WIAMIS
2009
IEEE
14 years 3 months ago
Towards fully un-supervised methods for generating object detection classifiers using social data
In this work a framework for constructing object detection classifiers using weakly annotated social data is proposed. Social information is combined with computer vision techniq...
Spiros Nikolopoulos, Elisavet Chatzilari, Eirini G...
ECCV
2004
Springer
14 years 10 months ago
Weak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
ATAL
2011
Springer
12 years 8 months ago
Towards a unifying characterization for quantifying weak coupling in dec-POMDPs
Researchers in the field of multiagent sequential decision making have commonly used the terms “weakly-coupled” and “loosely-coupled” to qualitatively classify problems i...
Stefan J. Witwicki, Edmund H. Durfee
ICPR
2004
IEEE
14 years 9 months ago
Nearest Neighbor Ensemble
Recent empirical work has shown that combining predictors can lead to significant reduction in generalization error. The individual predictors (weak learners) can be very simple, ...
Bojun Yan, Carlotta Domeniconi
ECCV
2006
Springer
13 years 10 months ago
Recognition and Segmentation of 3-D Human Action Using HMM and Multi-class AdaBoost
Our goal is to automatically segment and recognize basic human actions, such as stand, walk and wave hands, from a sequence of joint positions or pose angles. Such recognition is d...
Fengjun Lv, Ramakant Nevatia