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» A Robust Minimax Approach to Classification
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SIAMJO
2002
122views more  SIAMJO 2002»
13 years 8 months ago
Robust Filtering via Semidefinite Programming with Applications to Target Tracking
In this paper we propose a novel finite-horizon, discrete-time, time-varying filtering method based on the robust semidefinite programming (SDP) technique. The proposed method prov...
Lingjie Li, Zhi-Quan Luo, Timothy N. Davidson, Kon...
CVPR
2007
IEEE
14 years 11 months ago
Joint Object Segmentation and Behavior Classification in Image Sequences
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial fo...
Laura Gui, Jean-Philippe Thiran, Nikos Paragios
WSCG
2003
142views more  WSCG 2003»
13 years 10 months ago
Three-Dimensional Object Recognition: Statistical Approach
The design of a general purpose artificial vision system capable of recognizing arbitrarily complex threedimensional objects without human intervention is still a challenging task...
R. Abdul Salam, M. A. Rodrigues
ECCV
2000
Springer
14 years 11 months ago
Gray Scale and Rotation Invariant Texture Classification with Local Binary Patterns
This paper presents a theoretically very simple yet efficient approach for gray scale and rotation invariant texture classification based on local binary patterns and nonparametric...
Timo Ojala, Matti Pietikäinen, Topi Mäen...
JMLR
2008
104views more  JMLR 2008»
13 years 9 months ago
Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2
In this paper, the naive credal classifier, which is a set-valued counterpart of naive Bayes, is extended to a general and flexible treatment of incomplete data, yielding a new cl...
Giorgio Corani, Marco Zaffalon