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» Boosting Image Retrieval
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MIR
2010
ACM
207views Multimedia» more  MIR 2010»
14 years 11 months ago
Learning to rank for content-based image retrieval
In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking st...
Fabio F. Faria, Adriano Veloso, Humberto Mossri de...
104
Voted
ICIP
2002
IEEE
16 years 2 months ago
Content-based image retrieval for digital mammography
In this work, we explore the use of a learning-based framework for retrieval of relevant mammogram images from a database, for purposes of aiding diagnoses. A fundamental issue is...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
93
Voted
ICIP
2002
IEEE
16 years 2 months ago
Color texture moments for content-based image retrieval
In this paper, we adopt local Fourier transform as a texture representation scheme and derive eight characteristic maps for describing different aspects of co-occurrence relations...
Hui Yu, Mingjing Li, HongJiang Zhang, Jufu Feng
ICMCS
2006
IEEE
155views Multimedia» more  ICMCS 2006»
15 years 6 months ago
Region-Based Image Retrieval using Radial Basis Function Network
This paper presents a new framework that integrates relevance feedback into region-based image retrieval (RBIR) systems based on radial basis function network (RBFN). A modified u...
Kui Wu, Kim-Hui Yap, Lap-Pui Chau
133
Voted
ISM
2006
IEEE
209views Multimedia» more  ISM 2006»
15 years 6 months ago
Holistic Comparison of Text Images for Content-Based Retrieval
The accurate recognition of text that appears in images/videos using analytical character recognition methods is often very difficult, despite the fact that the text might be corr...
Julinda Gllavata, Ermir Qeli, Bernd Freisleben