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Relevance Feedback Content-Based Image Rertieval with Hierarchical Gaussian Process Bandits

Relevance Feedback Content-Based Image Rertieval with Hierarchical Gaussian Process Bandits

This video was recorded at Video Journal of Machine Learning Abstracts - Volume 4. A content-based image retrieval system based on relevance feedback is proposed. The system relies on an interactive search paradigm where at each round a user is presented with k images and selects the one closest to her target. The approach based on hierarchical Gaussian Process bandits is used to trade exploration and exploitation in presenting the images in each round. Experimental results show that the new approach compares favorably with previous work.
Keywords:
videolectures, ocwc, oec
Disciplines:
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More about this material

Material Type:
Presentation
Date Added to MERLOT:
February 10, 2015
Date Modified in MERLOT:
February 10, 2015
Author:
Submitter:
The Open Education Consortium
Primary Audience:
College General Ed, College Lower Division, College Upper Division
Technical Format:
Video
Mobile Compatibility:
Not specified at this time
Language:
English
Cost Involved:
No
Source Code Available:
No
Creative Commons:
Creative Commons License
This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States

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