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» Learning Models for Predicting Recognition Performance
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ECML
2005
Springer
15 years 3 months ago
Error-Sensitive Grading for Model Combination
Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
Surendra K. Singhi, Huan Liu
CVPR
2007
IEEE
15 years 11 months ago
Beyond bottom-up: Incorporating task-dependent influences into a computational model of spatial attention
A critical function in both machine vision and biological vision systems is attentional selection of scene regions worthy of further analysis by higher-level processes such as obj...
Robert J. Peters, Laurent Itti
ICASSP
2008
IEEE
15 years 4 months ago
Effective error prediction using decision tree for ASR grammar network in call system
CALL (Computer Assisted Language Learning) systems using ASR (Automatic Speech Recognition) for second language learning have received increasing interest recently. However, it st...
Hongcui Wang, Tatsuya Kawahara
ICRA
2006
IEEE
104views Robotics» more  ICRA 2006»
15 years 3 months ago
Implicit Coordination in Robotic Teams using Learned Prediction Models
— Many application tasks require the cooperation of two or more robots. Humans are good at cooperation in shared workspaces, because they anticipate and adapt to the intentions a...
Freek Stulp, Michael Isik, Michael Beetz
ITS
2010
Springer
165views Multimedia» more  ITS 2010»
15 years 2 months ago
Metacognition and Learning in Spoken Dialogue Computer Tutoring
We investigate whether four metacognitive metrics derived from student correctness and uncertainty values are predictive of student learning in a fully automated spoken dialogue co...
Katherine Forbes-Riley, Diane J. Litman