Skip to main navigation
Skip to search
Skip to main content
Illinois Experts Home
LOGIN & Help
Home
Profiles
Research units
Research & Scholarship
Datasets
Honors
Press/Media
Activities
Search by expertise, name or affiliation
One-class SVM for learning in image retrieval
Y. Chen, X. S. Zhou, T. S. Huang
Coordinated Science Lab
Research output
:
Contribution to conference
›
Paper
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'One-class SVM for learning in image retrieval'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Target Image
100%
Image Retrieval
100%
One-class Support Vector Machine (OCSVM)
100%
Relevance Feedback
66%
Tight
33%
Real Image
33%
Nonlinearity
33%
Image-based
33%
Feature Space
33%
Feedback Scheme
33%
Regularization Term
33%
In Content
33%
Positive Instances
33%
Retrieval Practice
33%
Hypersphere
33%
Content-based Image Retrieval
33%
Generalization Ability
33%
High-dimensional Feature Space
33%
Number of Training Samples
33%
Synthesized Data
33%
Linear Quadratic Estimator
33%
Computer Science
Image Retrieval
100%
Support Vector Machine
100%
Relevance Feedback
66%
Feature Space
33%
Regularization Term
33%
Dimensional Feature Space
33%
Training Sample
33%
retrieval performance
33%
Positive Example
33%
Content-based image retrieval
33%
Generalization Ability
33%
Engineering
Target Image
100%
Regularization
33%
Feature Space
33%
Nonlinearity
33%
Feedback Scheme
33%
Dimensional Feature Space
33%