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» Learning the Relative Importance of Features in Image Data
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BMVC
2010
13 years 6 months ago
Back to the Future: Learning Shape Models from 3D CAD Data
Recognizing 3D objects from arbitrary view points is one of the most fundamental problems in computer vision. A major challenge lies in the transition between the 3D geometry of o...
Michael Stark, Michael Goesele, Bernt Schiele
FGR
2008
IEEE
152views Biometrics» more  FGR 2008»
14 years 3 months ago
Facial feature detection with optimal pixel reduction SVM
Automatic facial feature localization has been a longstanding challenge in the field of computer vision for several decades. This can be explained by the large variation a face i...
Minh Hoai Nguyen, Joan Perez, Fernando De la Torre
ICASSP
2011
IEEE
13 years 12 days ago
Covariate-dependent dictionary learning and sparse coding
A dependent hierarchical beta process (dHBP) is developed as a prior for data that may be represented in terms of a sparse set of latent features (dictionary elements), with covar...
Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, Dav...
ECML
2001
Springer
14 years 1 months ago
A Framework for Learning Rules from Multiple Instance Data
Abstract. This paper proposes a generic extension to propositional rule learners to handle multiple-instance data. In a multiple-instance representation, each learning example is r...
Yann Chevaleyre, Jean-Daniel Zucker
BMCBI
2007
194views more  BMCBI 2007»
13 years 8 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung