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CGF
2005
252views more  CGF 2005»
13 years 8 months ago
Support Vector Machines for 3D Shape Processing
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Florian Steinke, Bernhard Schölkopf, Volker B...
CN
1999
143views more  CN 1999»
13 years 8 months ago
Embedding Knowledge in Web Documents
The paper argues for the use of general and intuitive knowledge representation languages (and simpler notational variants, e.g. subsets of natural languages) for indexing the cont...
Philippe Martin, Peter W. Eklund
ICLP
1990
Springer
14 years 23 days ago
Extending Definite Clause Grammars with Scoping Constructs
Definite Clause Grammars (DCGs) have proved valuable to computational linguists since they can be used to specify phrase structured grammars. It is well known how to encode DCGs i...
Remo Pareschi, Dale Miller
CVPR
2010
IEEE
14 years 5 months ago
Optimizing One-Shot Recognition with Micro-Set Learning
For object category recognition to scale beyond a small number of classes, it is important that algorithms be able to learn from a small amount of labeled data per additional clas...
Kevin Tang, Marshall Tappen, Rahul Sukthankar, Chr...
CVPR
2008
IEEE
14 years 10 months ago
Relaxed matching kernels for robust image comparison
The popular bag-of-features representation for object recognition collects signatures of local image patches and discards spatial information. Some have recently attempted to at l...
Andrea Vedaldi, Stefano Soatto