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130
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NIPS
2001
15 years 5 months ago
Categorization by Learning and Combining Object Parts
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
NIPS
2000
15 years 5 months ago
Learning Switching Linear Models of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Vladimir Pavlovic, James M. Rehg, John MacCormick
141
Voted
NAACL
1994
15 years 5 months ago
Language Identification via Large Vocabulary Speaker Independent Continuous Speech Recognition
The goal of this study is to evaluate the potential for using large vocabulary continuous speech recognition as an engine for automatically classifying utterances according to the...
Steve Lowe, Anne Demedts, Larry Gillick, Mark Mand...
MVA
1996
122views Computer Vision» more  MVA 1996»
15 years 5 months ago
Object Recognition from Range Images Using Superquadric Representations
Segmentation of range images using superquadric entities has been pointed out by a number of researchers as a powerful approach towards object recognition. Problems exist in findi...
Erik R. van Dop, Paul P. L. Regtien
118
Voted
AIR
2005
122views more  AIR 2005»
15 years 3 months ago
The Genetic Kernel Support Vector Machine: Description and Evaluation
The Support Vector Machine (SVM) has emerged in recent years as a popular approach to the classification of data. One problem that faces the user of an SVM is how to choose a kerne...
Tom Howley, Michael G. Madden