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114
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CGF
2010
153views more  CGF 2010»
15 years 19 days ago
Localized Delaunay Refinement for Sampling and Meshing
The technique of Delaunay refinement has been recognized as a versatile tool to generate Delaunay meshes of a variety of geometries. Despite its usefulness, it suffers from one la...
Tamal K. Dey, Joshua A. Levine, A. Slatton
95
Voted
BMCBI
2006
159views more  BMCBI 2006»
15 years 17 days ago
Prediction of protein continuum secondary structure with probabilistic models based on NMR solved structures
Background: The structure of proteins may change as a result of the inherent flexibility of some protein regions. We develop and explore probabilistic machine learning methods for...
Mikael Bodén, Zheng Yuan, Timothy L. Bailey
122
Voted
CVPR
2007
IEEE
16 years 2 months ago
Composite Models of Objects and Scenes for Category Recognition
This paper presents a method of learning and recognizing generic object categories using part-based spatial models. The models are multiscale, with a scene component that specifie...
David J. Crandall, Daniel P. Huttenlocher
95
Voted
ICIP
2006
IEEE
16 years 2 months ago
Local Discriminant Embedding with Tensor Representation
We present a subspace learning method, called Local Discriminant Embedding with Tensor representation (LDET), that addresses simultaneously the generalization and data representat...
Jian Xia, Dit-Yan Yeung, Guang Dai
118
Voted
CSL
2002
Springer
15 years 10 days ago
Learning visually grounded words and syntax for a scene description task
A spoken language generation system has been developed that learns to describe objects in computer-generated visual scenes. The system is trained by a `show-and-tell' procedu...
Deb K. Roy