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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 2 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
206
Voted
ICIP
2010
IEEE
14 years 11 months ago
Saliency detection using maximum symmetric surround
Detection of visually salient image regions is useful for applications like object segmentation, adaptive compression, and object recognition. Recently, full-resolution salient ma...
Radhakrishna Achanta, Sabine Süsstrunk
ACCV
2006
Springer
15 years 5 months ago
Motion Detection in Driving Environment Using U-V-Disparity
Abstract. Motion detection in driving environment, which aims to detect REAL moving objects from continuously changing background, is vital for Adaptive Cruise Control (ACC) applic...
Jia Wang, Zhencheng Hu, Hanqing Lu, Keiichi Uchimu...
CORR
2010
Springer
99views Education» more  CORR 2010»
15 years 2 months ago
An Automated Algorithm for Approximation of Temporal Video Data Using Linear B'EZIER Fitting
This paper presents an efficient method for approximation of temporal video data using linear Bezier fitting. For a given sequence of frames, the proposed method estimates the int...
Murtaza Ali Khan
CVPR
2008
IEEE
16 years 4 months ago
The Logistic Random Field - A convenient graphical model for learning parameters for MRF-based labeling
Graphical models are fundamental tools for modeling images and other applications. In this paper, we propose the Logistic Random Field (LRF) model for representing a discrete-valu...
Marshall F. Tappen, Kegan G. G. Samuel, Craig V. D...