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ICCV
2009
IEEE
13 years 6 months ago
A robust boosting tracker with minimum error bound in a co-training framework
The varying object appearance and unlabeled data from new frames are always the challenging problem in object tracking. Recently machine learning methods are widely applied to tra...
Rong Liu, Jian Cheng, Hanqing Lu
ICVS
2009
Springer
13 years 6 months ago
Boosting with a Joint Feature Pool from Different Sensors
This paper introduces a new way to apply boosting to a joint feature pool from different sensors, namely 3D range data and color vision. The combination of sensors strengthens the ...
Dominik Alexander Klein, Dirk Schulz, Simone Frint...
ADMA
2010
Springer
271views Data Mining» more  ADMA 2010»
13 years 4 months ago
Exploiting Concept Clumping for Efficient Incremental E-Mail Categorization
We introduce a novel approach to incremental e-mail categorization based on identifying and exploiting "clumps" of messages that are classified similarly. Clumping reflec...
Alfred Krzywicki, Wayne Wobcke
IJRR
2010
173views more  IJRR 2010»
13 years 3 months ago
Multi-modal Semantic Place Classification
The ability to represent knowledge about space and its position therein is crucial for a mobile robot. To this end, topological and semantic descriptions are gaining popularity fo...
Andrzej Pronobis, Óscar Martínez Moz...
TKDE
2010
224views more  TKDE 2010»
13 years 3 months ago
Non-Negative Matrix Factorization for Semisupervised Heterogeneous Data Coclustering
Coclustering heterogeneous data has attracted extensive attention recently due to its high impact on various important applications, such us text mining, image retrieval, and bioin...
Yanhua Chen, Lijun Wang, Ming Dong