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» Using Maximum Entropy for Automatic Image Annotation
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PAMI
2010
260views more  PAMI 2010»
13 years 6 months ago
Unsupervised Object Segmentation with a Hybrid Graph Model (HGM)
—In this work, we address the problem of performing class-specific unsupervised object segmentation, i.e., automatic segmentation without annotated training images. Object segmen...
Guangcan Liu, Zhouchen Lin, Yong Yu, Xiaoou Tang
ECCV
2004
Springer
14 years 9 months ago
Sparse Finite Elements for Geodesic Contours with Level-Sets
Level-set methods have been shown to be an effective way to solve optimisation problems that involve closed curves. They are well known for their capacity to deal with flexible top...
Martin Weber, Andrew Blake, Roberto Cipolla
JMM2
2007
127views more  JMM2 2007»
13 years 7 months ago
Robust Face Recognition through Local Graph Matching
— A novel face recognition method is proposed, in which face images are represented by a set of local labeled graphs, each containing information about the appearance and geometr...
Ehsan Fazl Ersi, John S. Zelek, John K. Tsotsos
BMCBI
2006
116views more  BMCBI 2006»
13 years 8 months ago
Optimized mixed Markov models for motif identification
Background: Identifying functional elements, such as transcriptional factor binding sites, is a fundamental step in reconstructing gene regulatory networks and remains a challengi...
Weichun Huang, David M. Umbach, Uwe Ohler, Leping ...
ICMCS
2007
IEEE
131views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Semantic Retrieval with Enhanced Matchmaking and Multi-Modality Ontology
This paper presents a method for automatically annotating and retrieving animal images. Our model is a multi-modality ontology extended from our previous works in the sense that b...
Huan Wang, Liang-Tien Chia, Song Liu