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» Boosting Methods for Regression
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ISI
2005
Springer
15 years 8 months ago
Selective Fusion for Speaker Verification in Surveillance
This paper presents an improved speaker verification technique that is especially appropriate for surveillance scenarios. The main idea is a metalearning scheme aimed at improving ...
Yosef A. Solewicz, Moshe Koppel
ICPR
2010
IEEE
15 years 4 months ago
Human-Area Segmentation by Selecting Similar Silhouette Images Based on Weak-Classifier Response
Human-area segmentation is a major issue in video surveillance. Many existing methods estimate individual human areas from the foreground area obtained by background subtraction, ...
Hiroaki Ando, Hironobu Fujiyoshi
ACL
1998
15 years 3 months ago
Using Decision Trees to Construct a Practical Parser
This paper describes novel and practical Japanese parsers that uses decision trees. First, we construct a single decision tree to estimate modification probabilities; how one phra...
Masahiko Haruno, Satoshi Shirai, Yoshifumi Ooyama
MCS
2002
Springer
15 years 2 months ago
Distributed Pasting of Small Votes
Bagging and boosting are two popular ensemble methods that achieve better accuracy than a single classifier. These techniques have limitations on massive datasets, as the size of t...
Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowye...
144
Voted
CVPR
2011
IEEE
14 years 6 months ago
Total Recall II: Query Expansion Revisited
Most effective particular object and image retrieval approaches are based on the bag-of-words (BoW) model. All state-of-the-art retrieval results have been achieved by methods tha...
Ondrej Chum, Andrej Mikulik, Michal Perdoch, Jiri ...