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» Using Linguistic Models for Image Retrieval
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MMDB
2004
ACM
148views Multimedia» more  MMDB 2004»
14 years 1 months ago
A unified framework for image database clustering and content-based retrieval
With the proliferation of image data, the need to search and retrieve images efficiently and accurately from a large image database or a collection of image databases has drastica...
Mei-Ling Shyu, Shu-Ching Chen, Min Chen, Chengcui ...
ICARCV
2006
IEEE
232views Robotics» more  ICARCV 2006»
14 years 1 months ago
Analysis of Relevance Feedback in Content Based Image Retrieval
: Relevance feedback in Content Based Image Retrieval(CBIR) has been an active field of research for quite some time now. Many schemes and techniques of relevance feedback exist w...
P. Suman Karthik, C. V. Jawahar
CBMS
2009
IEEE
13 years 11 months ago
A medical image retrieval framework in correlation enhanced visual concept feature space
This paper presents a medical image retrieval framework that uses visual concepts in a feature space employing statistical models built using a probabilistic multi-class support v...
Md. Mahmudur Rahman, Sameer Antani, George R. Thom...
ICDAR
2009
IEEE
13 years 5 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...
ESWA
2008
127views more  ESWA 2008»
13 years 7 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...