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» Improving Shape Retrieval by Learning Graph Transduction
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ICIP
2002
IEEE
15 years 2 months ago
A graphic-theoretic model for incremental relevance feedback in image retrieval
Many traditional relevance feedback approaches for CBIR can only achieve limited short-term performance improvement without benefiting long-term performance. To remedy this limita...
Yueting Zhuang, Jun Yang 0003, Qing Li, Yunhe Pan
107
Voted
ECCV
2008
Springer
15 years 11 months ago
Learning Visual Shape Lexicon for Document Image Content Recognition
Developing effective content recognition methods for diverse imagery continues to challenge computer vision researchers. We present a new approach for document image content catego...
Guangyu Zhu, Xiaodong Yu, Yi Li, David S. Doermann
95
Voted
CVPR
2012
IEEE
13 years 2 days ago
Learning to segment dense cell nuclei with shape prior
We study the problem of segmenting multiple cell nuclei from GFP or Hoechst stained microscope images with a shape prior. This problem is encountered ubiquitously in cell biology ...
Xinghua Lou, Ullrich Köthe, Jochen Wittbrodt,...
ISBI
2009
IEEE
15 years 4 months ago
Bridging the Semantic Gap Using Ranking Svm for Image Retrieval
One of the main challenges for Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings between the high-level semantic concepts and the low-level visual features in...
Haiying Guan, Sameer Antani, L. Rodney Long, Georg...
ECCB
2005
IEEE
15 years 3 months ago
A query language for biological networks
Many areas of modern biology are concerned with the management, storage, visualization, comparison, and analysis of networks. For instance, networks are used to model signal trans...
Ulf Leser