Learning Fine-Grained Image Similarity with Deep Ranking

Learning fine-grained image similarity is a challenging task. It needs to capture between-class and within-class image differences. This paper proposes a deep ranking model that employs deep learning techniques to learn similarity metric directly from images. It has higher learning capability than m...

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Bibliographic Details

Published in:	2014 IEEE Conference on Computer Vision and Pattern Recognition pp. 1386 - 1393
Main Authors:	Jiang Wang, Yang Song, Leung, Thomas, Rosenberg, Chuck, Jingbin Wang, Philbin, James, Bo Chen, Ying Wu
Format:	Conference Proceeding Journal Article
Language:	English
Published:	IEEE 01.06.2014
Subjects:	Algorithms Computational modeling Computer architecture Computer vision Conferences Learning Load modeling Mathematical models Neural networks Pattern recognition Ranking Semantics Similarity Training data Visualization
ISSN:	1063-6919, 1063-6919
Online Access:	Get full text
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