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CVPR
2008
IEEE
14 years 11 months ago
Boosting adaptive linear weak classifiers for online learning and tracking
Online boosting methods have recently been used successfully for tracking, background subtraction etc. Conventional online boosting algorithms emphasize on interchanging new weak ...
Toufiq Parag, Fatih Porikli, Ahmed M. Elgammal
CE
2007
113views more  CE 2007»
13 years 9 months ago
Research and development of web-based virtual online classroom
To build a web-based virtual learning environment depends on information technologies, concerns technology supporting learning methods and theories. A web-based virtual online cla...
Zongkai Yang, Qingtang Liu
PAMI
2007
194views more  PAMI 2007»
13 years 8 months ago
Robust Object Tracking Via Online Dynamic Spatial Bias Appearance Models
This paper presents a robust object tracking method via a spatial bias appearance model learned dynamically in video. Motivated by the attention shifting among local regions of a ...
Datong Chen, Jie Yang
ACL
2008
13 years 10 months ago
Active Learning with Confidence
Active learning is a machine learning approach to achieving high-accuracy with a small amount of labels by letting the learning algorithm choose instances to be labeled. Most of p...
Mark Dredze, Koby Crammer
AIRS
2008
Springer
14 years 3 months ago
Active Learning for Online Spam Filtering
Spam filtering is defined as a task trying to label emails with spam or ham in an online situation. The online feature requires the spam filter has a strong timely generalization a...
Wuying Liu, Ting Wang