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AAAI
2000
15 years 7 months ago
Redundancy in Random SAT Formulas
The random k-SAT model is extensively used to compare satisfiability algorithms or to find the best settings for the parameters of some algorithm. Conclusions are derived from the...
Yacine Boufkhad, Olivier Roussel
ICCV
2009
IEEE
16 years 11 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
ICCV
2009
IEEE
1048views Computer Vision» more  ICCV 2009»
16 years 11 months ago
Face Recognition With Contiguous Occlusion Using Markov Random Fields
Partially occluded faces are common in many applications of face recognition. While algorithms based on sparse representation have demonstrated promising results, they achieve t...
Zihan Zhou, Andrew Wagner, Hossein Mobahi, John Wr...
CVPR
2005
IEEE
16 years 8 months ago
Subspace Analysis Using Random Mixture Models
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
Xiaogang Wang, Xiaoou Tang
ICB
2009
Springer
412views Biometrics» more  ICB 2009»
16 years 29 days ago
Bayesian Face Recognition Based on Markov Random Field Modeling
In this paper, a Bayesian method for face recognition is proposed based on Markov Random Fields (MRF) modeling. Constraints on image features as well as contextual relationships be...
Rui Wang, Zhen Lei, Meng Ao, Stan Z. Li