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CVPR
2008
IEEE
15 years 12 months ago
Lost in quantization: Improving particular object retrieval in large scale image databases
The state of the art in visual object retrieval from large databases is achieved by systems that are inspired by text retrieval. A key component of these approaches is that local ...
James Philbin, Ondrej Chum, Michael Isard, Josef S...
ICASSP
2007
IEEE
15 years 4 months ago
A Radial Basis Function and Semantic Learning Space Based Composite Learning Approach to Image Retrieval
This paper introduces a composite learning approach for image retrieval with relevance feedback. The proposed system combines the radial basis function (RBF) based lowlevel learni...
Konstantin Shkurko, Xiaojun Qi
MMDB
2003
ACM
132views Multimedia» more  MMDB 2003»
15 years 3 months ago
Image database retrieval utilizing affinity relationships
Recent research effort in Content-Based Image Retrieval (CBIR) focuses on bridging the gap between low-level features and highlevel semantic contents of images as this gap has bec...
Mei-Ling Shyu, Shu-Ching Chen, Min Chen, Chengcui ...
MM
2004
ACM
219views Multimedia» more  MM 2004»
15 years 3 months ago
Multi-level annotation of natural scenes using dominant image components and semantic concepts
Automatic image annotation is a promising solution to enable semantic image retrieval via keywords. In this paper, we propose a multi-level approach to annotate the semantics of n...
Jianping Fan, Yuli Gao, Hangzai Luo
ICIP
2008
IEEE
15 years 11 months ago
Fast adaptive Mahalanobis distance-based search and retrieval in image databases
Motivated by the need to efficiently leverage user relevance feedback in content-based retrieval from image databases, we propose a fast, clustering-based indexing technique for e...
Sharadh Ramaswamy, Kenneth Rose