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» Textural Features and Relevance Feedback for Image Retrieval
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CIKM
2010
Springer
14 years 10 months ago
Learning to rank relevant and novel documents through user feedback
We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...
Abhimanyu Lad, Yiming Yang
ICIP
2007
IEEE
16 years 1 months ago
Using Phase and Magnitude Information of the Complex Directional Filter Bank for Texture Image Retrieval
This paper discusses how to utilize both magnitude and phase information obtained from the complex directional lter bank (CDFB) for the purpose of texture image retrieval. The rel...
An P. N. Vo, Soontorn Oraintara, Truong T. Nguyen
ICPR
2006
IEEE
16 years 27 days ago
Efficient Region Based Indexing and Retrieval for Images with Elastic Bucket Tries
Retrieval and indexing in multimedia databases has been an active topic both in the Information Retrieval and computer vision communities for a long time. In this paper we propose...
C. V. Jawahar, P. Suman Karthik
INEX
2004
Springer
15 years 5 months ago
TIJAH at INEX 2004 Modeling Phrases and Relevance Feedback
This paper discusses our participation in INEX using the TIJAH XML-IR system. We have enriched the TIJAH system, which follows a standard layered database architecture, with severa...
Vojkan Mihajlovic, Georgina Ramírez, Arjen ...
MTA
2008
146views more  MTA 2008»
14 years 11 months ago
A survey of browsing models for content based image retrieval
The problem of content based image retrieval (CBIR) has traditionally been investigated within a framework that emphasises the explicit formulation of a query: users initiate an au...
Daniel Heesch