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ICDE
2000
IEEE
189views Database» more  ICDE 2000»
16 years 6 months ago
Image Database Retrieval with Multiple-Instance Learning Techniques
In this paper, we develop and test an approach to retrieving images from an image database based on content similarity. First, each picture is divided into many overlapping region...
Cheng Yang, Tomás Lozano-Pérez
CBMS
2003
IEEE
15 years 10 months ago
Localizing Contour Points for Indexing an X-Ray Image Retrieval System
Vertebra shape can effectively describe various pathologies found in spine x-ray images. There are some critical regions on the shape contour which help determine whether the shap...
Xiaoqian Xu, D. J. Lee, Sameer Antani, L. Rodney L...
APWEB
2003
Springer
15 years 9 months ago
Web-Based Image Retrieval with a Case Study
Abstract. Advances in content-based image retrieval(CBIR)lead to numerous efficient techniques for retrieving images based on their content features, such as colours, textures and ...
Ying Liu, Danqing Zhang
CVPR
2004
IEEE
15 years 8 months ago
Learning in Region-Based Image Retrieval with Generalized Support Vector Machines
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...
Iker Gondra, Douglas R. Heisterkamp
ESWA
2008
127views more  ESWA 2008»
15 years 4 months ago
A two-level relevance feedback mechanism for image retrieval
Content-based image retrieval (CBIR) is a group of techniques that analyzes the visual features (such as color, shape, texture) of an example image or image subregion to find simi...
Pei-Cheng Cheng, Been-Chian Chien, Hao-Ren Ke, Wei...