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ICMCS
2005
IEEE
221views Multimedia» more  ICMCS 2005»
13 years 10 months ago
A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
WEBI
2010
Springer
13 years 2 months ago
Image Set Classification Using Multi-layer Multiple Instance Learning with Application to Cannabis Website Classification
We propose using multi-layer multiple instance learning (MMIL) for image set classification and applying it to the task of cannabis website classification. We treat each image as a...
Nianhua Xie, Haibin Ling, Weiming Hu
ICIAR
2005
Springer
13 years 10 months ago
Machine-Learning-Based Image Categorization
In this paper, a novel and efficient automatic image categorization system is proposed. This system integrates the MIL-based and global-featurebased SVMs for categorization. The IP...
Yutao Han, Xiaojun Qi
CVPR
2006
IEEE
13 years 8 months ago
Region-based Image Annotation using Asymmetrical Support Vector Machine-based Multiple-Instance Learning
In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning...
Changbo Yang, Ming Dong, Jing Hua
ICDE
2000
IEEE
189views Database» more  ICDE 2000»
14 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