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CIVR
2005
Springer
123views Image Analysis» more  CIVR 2005»
13 years 10 months ago
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Chengcui Zhang, Xin Chen
VCIP
2003
238views Communications» more  VCIP 2003»
13 years 6 months ago
Texture segmentation based on features in wavelet domain for image retrieval
Texture is a fundamental feature which provides significant information for image classification, and is an important content used in content-based image retrieval (CBIR) system. ...
Ying Liu, Si Wu, Xiaofang Zhou
PAKDD
2009
ACM
263views Data Mining» more  PAKDD 2009»
14 years 2 days ago
Spatial Weighting for Bag-of-Visual-Words and Its Application in Content-Based Image Retrieval
It is a challenging and important task to retrieve images from a large and highly varied image data set based on their visual contents. Problems like how to fill the semantic gap b...
Xin Chen, Xiaohua Hu, Xiajiong Shen
SAC
2002
ACM
13 years 5 months ago
Color patterns for pictorial content description
In this paper, we propose a new type of image feature, which consists of patterns of colors and intensities that capture the latent associations among images and primitive feature...
Daniela Stan, Ishwar K. Sethi
MIR
2006
ACM
145views Multimedia» more  MIR 2006»
13 years 11 months ago
Similarity learning via dissimilarity space in CBIR
In this paper, we introduce a new approach to learn dissimilarity for interactive search in content based image retrieval. In literature, dissimilarity is often learned via the fe...
Giang P. Nguyen, Marcel Worring, Arnold W. M. Smeu...