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» Optimizing Learning in Image Retrieval
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ICIP
2007
IEEE
14 years 3 months ago
Weighted Co-SVM for Image Retrieval with MVB Strategy
In relevance feedback, active learning is often used to alleviate the burden of labeling by selecting only the most informative data. Traditional data selection strategies often c...
Xiaoyu Zhang, Jian Cheng, Hanqing Lu, Songde Ma
CLEF
2008
Springer
13 years 10 months ago
Using Visual Concepts and Fast Visual Diversity to Improve Image Retrieval
In this article, we focus our efforts (i) on the study of how to automatically extract and exploit visual concepts and (ii) on fast visual diversity. First, in the Visual Concept D...
Sabrina Tollari, Marcin Detyniecki, Ali Fakeri-Tab...
ICDAR
2009
IEEE
13 years 6 months ago
Handwritten Word Image Retrieval with Synthesized Typed Queries
We propose a new method for handwritten word-spotting which does not require prior training or gathering examples for querying. More precisely, a model is trained "on the fly...
José A. Rodríguez-Serrano, Florent P...
CIVR
2008
Springer
222views Image Analysis» more  CIVR 2008»
13 years 10 months ago
Automatic image annotation via local multi-label classification
As the consequence of semantic gap, visual similarity does not guarantee semantic similarity, which in general is conflicting with the inherent assumption of many generativebased ...
Mei Wang, Xiangdong Zhou, Tat-Seng Chua
ICIP
2003
IEEE
14 years 10 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