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» Expectation Maximization and Posterior Constraints
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CVPR
2004
IEEE
14 years 11 months ago
Hidden Semantic Concept Discovery in Region Based Image Retrieval
This paper addresses Content Based Image Retrieval (CBIR), focusing on developing a hidden semantic concept discovery methodology to address effective semanticsintensive image ret...
Ruofei Zhang, Zhongfei (Mark) Zhang
ICDM
2006
IEEE
76views Data Mining» more  ICDM 2006»
14 years 3 months ago
A Probabilistic Ensemble Pruning Algorithm
An ensemble is a group of learners that work together as a committee to solve a problem. However, the existing ensemble training algorithms sometimes generate unnecessary large en...
Huanhuan Chen, Peter Tiño, Xin Yao
CVPR
2012
IEEE
12 years 1 days ago
Maximum weight cliques with mutex constraints for video object segmentation
In this paper, we address the problem of video object segmentation, which is to automatically identify the primary object and segment the object out in every frame. We propose a n...
Tianyang Ma, Longin Jan Latecki
MICCAI
2010
Springer
13 years 8 months ago
Non-parametric Iterative Model Constraint Graph min-cut for Automatic Kidney Segmentation
We present a new non-parametric model constraint graph min-cut algorithm for automatic kidney segmentation in CT images. The segmentation is formulated as a maximum a-posteriori es...
Moti Freiman, A. Kronman, S. J. Esses, Leo Joskowi...
CVPR
2012
IEEE
12 years 1 days ago
Active image clustering: Seeking constraints from humans to complement algorithms
We propose a method of clustering images that combines algorithmic and human input. An algorithm provides us with pairwise image similarities. We then actively obtain selected, mo...
Arijit Biswas, David W. Jacobs