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» Relevance Ranking Metrics for Learning Objects
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ICIP
2003
IEEE
15 years 11 months ago
Performance evaluation of Euclidean/correlation-based relevance feedback algorithms in content-based image retrieval systems
In this paper, we evaluate and investigate two main types of relevance feedback algorithms; the Euclidean and the correlation?based approaches. In the first case, we examine heuri...
Anastasios D. Doulamis, Nikolaos D. Doulamis
ICASSP
2011
IEEE
14 years 1 months ago
Topic-sensitive interactive image object retrieval with noise-proof relevance feedback
One current direction to enhance the search accuracy in visual object retrieval is to reformulate the original query through (pseudo-)relevance feedback, which augments a query wi...
Jen-Hao Hsiao, Henry Chang
76
Voted
ICIP
2002
IEEE
15 years 11 months ago
Extraction of semantic objects from still images
In this work, we study the extraction of semantic objects from still images. We combine different ideas to extract them in a structured manner together with a perceptual metric th...
Alvaro Pardo
CVPR
2001
IEEE
15 years 11 months ago
Learning Similarity Measure for Natural Image Retrieval with Relevance Feedback
A new scheme of learning similarity measure is proposed for content-based image retrieval (CBIR). It learns a boundary that separates the images in the database into two parts. Im...
Guodong Guo, Anil K. Jain, Wei-Ying Ma, HongJiang ...
110
Voted
ICCV
2009
IEEE
14 years 7 months ago
Efficient multi-label ranking for multi-class learning: Application to object recognition
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Ron...