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ICIP
2000
IEEE
14 years 9 months ago
Incorporate Support Vector Machines to Content-Based Image Retrieval with Relevant Feedback
By using relevance feedback [6], Content-Based Image Retrieval (CBIR) allows the user to retrieve images interactively. The user can select the most relevant images and provide a ...
Pengyu Hong, Qi Tian, Thomas S. Huang
MM
2004
ACM
178views Multimedia» more  MM 2004»
14 years 24 days ago
A bootstrapping framework for annotating and retrieving WWW images
Most current image retrieval systems and commercial search engines use mainly text annotations to index and retrieve WWW images. This research explores the use of machine learning...
HuaMin Feng, Rui Shi, Tat-Seng Chua
CIVR
2005
Springer
123views Image Analysis» more  CIVR 2005»
14 years 28 days 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
ICMCS
2005
IEEE
221views Multimedia» more  ICMCS 2005»
14 years 29 days 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...
MIR
2003
ACM
178views Multimedia» more  MIR 2003»
14 years 19 days ago
A bootstrapping approach to annotating large image collection
Huge amount of manual efforts are required to annotate large image/video archives with text annotations. Several recent works attempted to automate this task by employing supervis...
HuaMin Feng, Tat-Seng Chua