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» Relevance Feedback in XML Retrieval
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VDB
1998
117views Database» more  VDB 1998»
13 years 8 months ago
Textural Features and Relevance Feedback for Image Retrieval
This paper focuses on the retrieval of complex images based on their textural content. We use GMRF for texture discrimination and a region-growing algorithm for texture segmentati...
Eugenio Di Sciascio, Giacomo Piscitelli, Augusto C...
CVPR
2004
IEEE
14 years 8 months ago
Random Sampling Based SVM for Relevance Feedback Image Retrieval
Relevance feedback (RF) schemes based on support vector machine (SVM) have been widely used in content-based image retrieval. However, the performance of SVM based RF is often poo...
Dacheng Tao, Xiaoou Tang
CIVR
2008
Springer
127views Image Analysis» more  CIVR 2008»
13 years 8 months ago
Performance evaluation of relevance feedback methods
In this paper we review the evaluation of relevance feedback methods for content-based image retrieval systems. We start out by presenting an overview of current common practice, ...
Mark J. Huiskes, Michael S. Lew
MM
2006
ACM
164views Multimedia» more  MM 2006»
14 years 20 days ago
Scalable relevance feedback using click-through data for web image retrieval
Relevance feedback (RF) has been extensively studied in the content-based image retrieval community. However, no commercial Web image search engines support RF because of scalabil...
En Cheng, Feng Jing, Lei Zhang, Hai Jin
ESWA
2008
127views more  ESWA 2008»
13 years 6 months ago
A two-level relevance feedback mechanism for image retrieval
Content-based image retrieval (CBIR) is a group of techniques that analyzes the visual features (such as color, shape, texture) of an example image or image subregion to find simi...
Pei-Cheng Cheng, Been-Chian Chien, Hao-Ren Ke, Wei...