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PAMI
2010
265views more  PAMI 2010»
13 years 7 months ago
Motion Segmentation in the Presence of Outlying, Incomplete, or Corrupted Trajectories
—In this paper, we study the problem of segmenting tracked feature point trajectories of multiple moving objects in an image sequence. Using the affine camera model, this proble...
Shankar Rao, Roberto Tron, René Vidal, Yi M...
CVPR
2006
IEEE
14 years 10 months ago
Unsupervised Learning of Categories from Sets of Partially Matching Image Features
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Kristen Grauman, Trevor Darrell
CVPR
2010
IEEE
14 years 4 months ago
An automatic unsupervised classification of MR images in Alzheimer's disease
Image-analysis methods play an important role in helping detect brain changes in and diagnosis of Alzheimer's Disease (AD). In this paper, we propose an automatic unsupervised...
Xiaojing Long
SDM
2008
SIAM
176views Data Mining» more  SDM 2008»
13 years 10 months ago
A General Model for Multiple View Unsupervised Learning
Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang
BMCBI
2008
142views more  BMCBI 2008»
13 years 8 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu