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MVA
2007
154views Computer Vision» more  MVA 2007»
15 years 5 months ago
Fisher Non-negative Matrix Factorization with Pairwise Weighting
Non-negative matrix factorization (NMF) is a powerful feature extraction method for finding parts-based, linear representations of non-negative data . Inherently, it is unsupervis...
Xi Li, Kazuhiro Fukui
IJON
2002
85views more  IJON 2002»
15 years 3 months ago
Learning statistically efficient features for speaker recognition
We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for a speaker. The basis functions learned by the algori...
Gil-Jin Jang, Te-Won Lee, Yung-Hwan Oh
150
Voted
ECCV
2008
Springer
16 years 5 months ago
Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features
Viewpoint invariant pedestrian recognition is an important yet under-addressed problem in computer vision. This is likely due to the difficulty in matching two objects with unknown...
Douglas Gray, Hai Tao
167
Voted
ICDAR
2011
IEEE
14 years 3 months ago
Co-training for Handwritten Word Recognition
—To cope with the tremendous variations of writing styles encountered between different individuals, unconstrained automatic handwriting recognition systems need to be trained on...
Volkmar Frinken, Andreas Fischer, Horst Bunke, Ali...
137
Voted
WIA
2005
Springer
15 years 9 months ago
Learning Stochastic Finite Automata for Musical Style Recognition
Abstract. Stochastic deterministic finite automata have been introduced and are used in a variety of settings. We use them to model musical styles: a same automaton can be used to...
Colin de la Higuera, Frédéric Piat, ...