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» A Support Vector Clustering Method
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134
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TNN
2008
178views more  TNN 2008»
15 years 3 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
BMCBI
2004
133views more  BMCBI 2004»
15 years 3 months ago
Esub8: A novel tool to predict protein subcellular localizations in eukaryotic organisms
Background: Subcellular localization of a new protein sequence is very important and fruitful for understanding its function. As the number of new genomes has dramatically increas...
Qinghua Cui, Tianzi Jiang, Bing Liu, Songde Ma
MP
2002
195views more  MP 2002»
15 years 2 months ago
Nonlinear rescaling vs. smoothing technique in convex optimization
We introduce an alternative to the smoothing technique approach for constrained optimization. As it turns out for any given smoothing function there exists a modification with part...
Roman A. Polyak
ACCV
2010
Springer
14 years 10 months ago
Randomised Manifold Forests for Principal Angle-Based Face Recognition
Abstract. In set-based face recognition, each set of face images is often represented as a linear/nonlinear manifold and the Principal Angles (PA) or Kernel PAs are exploited to me...
Ujwal D. Bonde, Tae-Kyun Kim, K. R. Ramakrishnan
182
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CVPR
2009
IEEE
16 years 10 months ago
Learning Semantic Visual Vocabularies Using Diffusion Distance
In this paper, we propose a novel approach for learning generic visual vocabulary. We use diffusion maps to au-tomatically learn a semantic visual vocabulary from ab-undant quantiz...
Jingen Liu (University of Central Florida), Yang Y...