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» Learning Flexible Features for Conditional Random Fields
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ICASSP
2011
IEEE
14 years 5 months ago
Automatic speech recognition using Hidden Conditional Neural Fields
Hidden Conditional Random Fields(HCRF) is a very promising approach to model speech. However, because HCRF computes the score of a hypothesis by summing up linearly weighted featu...
Yasuhisa Fujii, Kazumasa Yamamoto, Seiichi Nakagaw...
ICDAR
2005
IEEE
15 years 7 months ago
Learning Diagram Parts with Hidden Random Fields
Many diagrams contain compound objects composed of parts. We propose a recognition framework that learns parts in an unsupervised way, and requires training labels only for compou...
Martin Szummer
IJCV
2008
266views more  IJCV 2008»
15 years 1 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
ICALT
2009
IEEE
15 years 4 months ago
Conditioning Factors for Group Management in Blended Learning Scenarios
The management of groups is an essential task in collaborative learning scenarios. In a blended learning situation, in which online activities and face-to-face activities are comb...
Mar Pérez-Sanagustín, Davinia Hern&a...
MLMI
2007
Springer
15 years 7 months ago
Conditional Sequence Model for Context-Based Recognition of Gaze Aversion
Eye gaze and gesture form key conversational grounding cues that are used extensively in face-to-face interaction among people. To accurately recognize visual feedback during inter...
Louis-Philippe Morency, Trevor Darrell