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» Features for image retrieval: an experimental comparison
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CVPR
2005
IEEE
14 years 1 months ago
Mapping Low-Level Features to High-Level Semantic Concepts in Region-Based Image Retrieval
In this a novel supervised learning method is proposed to map low-level visualfeatures to high-level semantic conceptsfor region-based image retrieval. The contributions of thispa...
Wei Jiang, Kap Luk Chan, Mingjing Li, HongJiang Zh...
CIKM
2010
Springer
13 years 6 months ago
Novel local features with hybrid sampling technique for image retrieval
In image retrieval, most existing approaches that incorporate local features produce high dimensional vectors, which lead to a high computational and data storage cost. Moreover, ...
Leszek Kaliciak, Dawei Song, Nirmalie Wiratunga, J...
ICIP
1999
IEEE
14 years 9 months ago
Water-Filling: A Novel Way for Image Structural Feature Extraction
The performance of a content based image retrieval (CBIR) system is inherently constrained by the features adopted to represent the images in the database. In this paper, a new ap...
Xiang Sean Zhou, Yong Rui, Thomas S. Huang
ICPR
2006
IEEE
14 years 8 months ago
Near-Duplicate Image Recognition and Content-based Image Retrieval using Adaptive Hierarchical Geometric Centroids
In this paper, we present a new feature extraction method that simultaneously captures the global and local characteristics of an image by adaptively computing hierarchical geomet...
Dave Elliman, Guoping Qiu, Jiwu Huang, Mai Yang
SIGIR
2009
ACM
14 years 1 months ago
A comparison of retrieval-based hierarchical clustering approaches to person name disambiguation
This paper describes a simple clustering approach to person name disambiguation of retrieved documents. The methods are based on standard IR concepts and do not require any task-s...
Christof Monz, Wouter Weerkamp