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Machine Vision and Applications
Published in: Machine Vision and Applications 1/2019

30-10-2018 | Original paper

Weighted-learning-instance-based retrieval model using instance distance

Authors: Hao Wu, Yueli Li, Jie Xiong, Xiaohan Bi, Linna Zhang, Rongfang Bie, Junqi Guo

Published in: Machine Vision and Applications | Issue 1/2019

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Abstract

High-quality retrieval techniques can effectively retrieve target images from millions of images, and some classic techniques are widely used in different fields. As a classic image retrieval technique, deep learning shows remarkable advantages in significantly improving retrieval results. However, high-quality retrieval results highly depend on sufficient learning instances. When no sufficient learning instances exist to support learning model construction, then retrieval quality reduces remarkably. In most cases, sufficient learning instances lead to wasting of significant computing and human resources. Aiming at the aforementioned problem, we proposed a weighted-learning-instance-based retrieval model requiring instance distance calculation. Concretely, reference learning instance optimization, instance distance calculation, and innovative cost function construction are combined which could directly contribute to build up the previous model. Firstly, high-quality reference learning instances could be selected by learning instance optimization model. Then, combined with weights of learning instances calculated by instance distance, the innovative cost function could be constructed which could make full use of learning instances under various circumstances. More importantly, this model can significantly reduce the number of learning instances through instance optimization and weight definition while maintaining high level of retrieval quality. Adequate experimental results based on a large database show robustness and effectiveness of our model.
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Metadata
Title
Weighted-learning-instance-based retrieval model using instance distance
Authors
Hao Wu
Yueli Li
Jie Xiong
Xiaohan Bi
Linna Zhang
Rongfang Bie
Junqi Guo
Publication date
30-10-2018
Publisher
Springer Berlin Heidelberg
Published in
Machine Vision and Applications / Issue 1/2019
Print ISSN: 0932-8092
Electronic ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-018-0988-x

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