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ICMCS
2000
IEEE
142views Multimedia» more  ICMCS 2000»
15 years 2 months ago
Incorporate Discriminant Analysis with EM Algorithm in Image Retrieval
One of the difficulties of Content-Based Image Retrieval (CBIR) is the gap between high-level concepts and low-level image features, e.g., color and texture. Relevance feedback wa...
Qi Tian, Ying Wu, Thomas S. Huang
WACV
2012
IEEE
13 years 5 months ago
Tools for richer crowd source image annotations
Crowd-sourcing tools such as Mechanical Turk are popular for annotation of large scale image data sets. Typically, these annotations consist of bounding boxes or coarse outlines o...
Joshua Little, Austin Abrams, Robert Pless
CIVR
2005
Springer
15 years 3 months ago
Automatic Annotation of Images from the Practitioner Perspective
This paper describes an ongoing project which seeks to contribute to a wider understanding of the realities of bridging the semantic gap in visual image retrieval. A comprehensive ...
Peter G. B. Enser, Christine J. Sandom, Paul H. Le...
MMM
2003
Springer
146views Multimedia» more  MMM 2003»
15 years 3 months ago
An Improved Method for Image Retrieval Using Speech Annotation
In this paper, we present a system for the image indexing and retrieval using speech annotations based on a pre-defined
Jiayi Chen, Tele Tan
ISCIS
2009
Springer
15 years 4 months ago
Dynamic feature weights with relevance feedback in content-based image retrieval
— In this paper, we present a novel relevance feedback method for Content-Based Image Retrieval systems based on dynamic feature weights. The proposed method utilizes intracluste...
Esin Guldogan, Moncef Gabbouj