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» Boosting Image Retrieval
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116
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DRR
2008
15 years 2 months ago
Segmentation-based retrieval of document images from diverse collections
We describe a methodology for retrieving document images from large extremely diverse collections. First we perform content extraction, that is the location and measurement of reg...
Michael A. Moll, Henry S. Baird
CIVR
2007
Springer
177views Image Analysis» more  CIVR 2007»
15 years 7 months ago
Matching ottoman words: an image retrieval approach to historical document indexing
Large archives of Ottoman documents are challenging to many historians all over the world. However, these archives remain inaccessible since manual transcription of such a huge vo...
Esra Ataer, Pinar Duygulu
110
Voted
ICPR
2000
IEEE
16 years 1 months ago
Feature Relevance Learning with Query Shifting for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai
CVPR
2004
IEEE
16 years 2 months ago
Random Sampling Based SVM for Relevance Feedback Image Retrieval
Relevance feedback (RF) schemes based on support vector machine (SVM) have been widely used in content-based image retrieval. However, the performance of SVM based RF is often poo...
Dacheng Tao, Xiaoou Tang
115
Voted
MM
2005
ACM
171views Multimedia» more  MM 2005»
15 years 6 months ago
Semantic manifold learning for image retrieval
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
Yen-Yu Lin, Tyng-Luh Liu, Hwann-Tzong Chen