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» Boosting Methods for Regression
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ISI
2005
Springer
14 years 3 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
14 years 3 days 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
13 years 11 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
13 years 9 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...
CVPR
2011
IEEE
13 years 1 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 ...