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ESANN
2004
15 years 8 months ago
Online policy adaptation for ensemble classifiers
Ensemble algorithms can improve the performance of a given learning algorithm through the combination of multiple base classifiers into an ensemble. In this paper, the idea of usin...
Christos Dimitrakakis, Samy Bengio
ECCV
2008
Springer
16 years 9 months ago
Semi-supervised On-Line Boosting for Robust Tracking
Abstract. Recently, on-line adaptation of binary classifiers for tracking have been investigated. On-line learning allows for simple classifiers since only the current view of the ...
Helmut Grabner, Christian Leistner, Horst Bischof
ICALT
2007
IEEE
16 years 1 months ago
Finding the Right Tool for the Community: Bringing a Wiki-Type Editor to the World of Reusable Learning Objects
In this paper we present a new approach to enabling pedagogically sound reuse and re-purposing of online learning objects in a community of practice. The lack of specific software...
Chu Wang, Hugh C. Davis, Kate Dickens, Gary Wills,...
CVPR
2007
IEEE
15 years 11 months ago
Improving Part based Object Detection by Unsupervised, Online Boosting
Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
Bo Wu, Ram Nevatia
185
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ICCV
2009
IEEE
17 years 2 days 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...