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» Learning Flexible Features for Conditional Random Fields
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ICASSP
2011
IEEE
14 years 1 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 3 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»
14 years 9 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 27 days 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 3 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