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CVIU
2004
115views more  CVIU 2004»
15 years 4 months ago
Dynamic learning from multiple examples for semantic object segmentation and search
We present a novel ``dynamic learning'' approach for an intelligent image database system to automatically improve object segmentation and labeling without user interven...
Yaowu Xu, Eli Saber, A. Murat Tekalp
ML
2007
ACM
153views Machine Learning» more  ML 2007»
15 years 4 months ago
Multi-Class Learning by Smoothed Boosting
AdaBoost.OC has been shown to be an effective method in boosting “weak” binary classifiers for multi-class learning. It employs the Error-Correcting Output Code (ECOC) method ...
Rong Jin, Jian Zhang 0003
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
15 years 2 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer
AI
2011
Springer
14 years 8 months ago
Learning Dialogue POMDP Models from Data
In this paper, we learn the components of dialogue POMDP models from data. In particular, we learn the states, observations, as well as transition and observation functions based o...
Hamid R. Chinaei, Brahim Chaib-draa
FGR
2008
IEEE
170views Biometrics» more  FGR 2008»
15 years 11 months ago
Using an adaptive VAR Model for motion prediction in 3D hand tracking
A robust VAR-based (vector autoregressive) model is introduced for motion prediction in 3D hand tracking. This dynamic VAR motion model is learned in an online manner. The kinemat...
Desmond Chik, Jochen Trumpf, Nicol N. Schraudolph