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» A two-level relevance feedback mechanism for image retrieval
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PRL
2000
104views more  PRL 2000»
14 years 9 months ago
PicSOM - content-based image retrieval with self-organizing maps
We have developed a novel system for content-based image retrieval in large, unannotated databases. The system is called PicSOM, and it is based on tree structured self-organizing...
Jorma Laaksonen, Markus Koskela, Sami Laakso, Erkk...
83
Voted
ICITA
2005
IEEE
15 years 3 months ago
Combining Diversity-Based Active Learning with Discriminant Analysis in Image Retrieval
Small-sample learning in image retrieval is a pertinent and interesting problem. Relevance feedback is an active area of research that seeks to find algorithms that are robust wi...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
CIVR
2004
Springer
166views Image Analysis» more  CIVR 2004»
15 years 3 months ago
Object Segmentation and Ontologies for MPEG-2 Video Indexing and Retrieval
Abstract. A novel approach to object-based video indexing and retrieval is presented, employing an object segmentation algorithm for the real-time, unsupervised segmentation of com...
Vasileios Mezaris, Michael G. Strintzis
PRL
2008
143views more  PRL 2008»
14 years 9 months ago
An active feedback framework for image retrieval
In recent years, relevance feedback has been studied extensively as a way to improve performance of content-based image retrieval (CBIR). Since users are usually unwilling to prov...
Tao Qin, Xu-Dong Zhang, Tie-Yan Liu, De-Sheng Wang...
96
Voted
ICCV
2003
IEEE
15 years 3 months ago
Reinforcement Learning for Combining Relevance Feedback Techniques
Relevance feedback (RF) is an interactive process which refines the retrievals by utilizing user’s feedback history. Most researchers strive to develop new RF techniques and ign...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...