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» Support Vector Machines Applied to Face Recognition
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PRL
2008
93views more  PRL 2008»
13 years 8 months ago
Learning to learn: From smart machines to intelligent machines
Since its birth, more than five decades ago, one of the biggest challenges of artificial intelligence remained the building of intelligent machines. Despite amazing advancements, ...
Bogdan Raducanu, Jordi Vitrià
ICIP
2005
IEEE
14 years 9 months ago
Generalized Histogram Intersection Kernel for Image Recognition
Histogram Intersection (HI) kernel has been recently introduced for image recognition tasks. The HI kernel is proved to be positive definite and thus can be used in Support Vector ...
Sabri Boughorbel, Jean-Philippe Tarel and Nozha Bo...
AMFG
2007
IEEE
328views Biometrics» more  AMFG 2007»
14 years 2 months ago
Fusing Gabor and LBP Feature Sets for Kernel-Based Face Recognition
Extending recognition to uncontrolled situations is a key challenge for practical face recognition systems. Finding efficient and discriminative facial appearance descriptors is c...
Xiaoyang Tan, Bill Triggs
ICIP
2010
IEEE
13 years 6 months ago
A close-up detection method for movies
Close-up (CU) is a photographic technique which tightly frames a person or an object. In movies, it is applied to guide audience attention and to evoke audience emotion. In this p...
Huiying Liu, Min Xu, Qingming Huang, Jesse S. Jin,...
BMCBI
2008
138views more  BMCBI 2008»
13 years 8 months ago
Application of nonnegative matrix factorization to improve profile-profile alignment features for fold recognition and remote ho
Background: Nonnegative matrix factorization (NMF) is a feature extraction method that has the property of intuitive part-based representation of the original features. This uniqu...
Inkyung Jung, Jaehyung Lee, Soo-Young Lee, Dongsup...