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» Image Based Regression Using Boosting Method
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ICMCS
2009
IEEE
189views Multimedia» more  ICMCS 2009»
14 years 7 months ago
Emotion recognition from speech VIA boosted Gaussian mixture models
Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...
SIGIR
2011
ACM
14 years 17 days ago
A boosting approach to improving pseudo-relevance feedback
Pseudo-relevance feedback has proven effective for improving the average retrieval performance. Unfortunately, many experiments have shown that although pseudo-relevance feedback...
Yuanhua Lv, ChengXiang Zhai, Wan Chen
ICIP
2007
IEEE
15 years 11 months ago
Do Colour Interest Points Improve Image Retrieval?
In image retrieval scenarios, many methods use interest point detection at an early stage to find regions in which descriptors are calculated. Finding salient locations in image d...
Allan Hanbury, Julian Stöttinger, Nicu Sebe, ...
ICPR
2008
IEEE
15 years 4 months ago
Regression with interval output values
We consider a regression problem where target values are given as intervals, and propose a statistical approach to it. Although it is hard to solve the optimization problem direct...
Hisashi Kashima, Kazutaka Yamasaki, Akihiro Inokuc...
ENTCS
2007
116views more  ENTCS 2007»
14 years 9 months ago
Handling Model Changes: Regression Testing and Test-Suite Update with Model-Checkers
Several model-checker based methods to automated test-case generation have been proposed recently. The performance and applicability largely depends on the complexity of the model...
Gordon Fraser, Bernhard K. Aichernig, Franz Wotawa