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2018 | OriginalPaper | Chapter

An Image Retrieval Algorithm Based on Semantic Self-Feedback Mechanism

Authors : Lang Pei, Jia Xu, Jinhua Cai

Published in: Advances in Intelligent Systems and Interactive Applications

Publisher: Springer International Publishing

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Abstract

According to the image retrieval process the user need to submit many times and feedback the query, based on semantic correlation self-feedback algorithm, a user submits the demand, active feedback query, finally get to meet the needs of the results, simplify the query process, Enhanced the “fool” feature of the image retrieval system. The test results show that the algorithm has higher accuracy and higher flexibility.

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previous chapter Super-resolution Reconstruction of Face Image Based on Convolution Network
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Literature
1.
Zhu, L.: Geoblock: a LVQ-Based Framework for Geographic Image Retrieval, Information Technology: Coding and Computing, Proceedings. ITCC 2004, pp. 156–163 (2004)
2.
Praks, P., Snasel, V., Dvorsky, J., Cernohorsky, J.: On SVD-free latent semantic indexing for image retrieval for application in a hard industrial environment industrial technology. In: IEEE International Conference on Volume 1, 10–12 Doc, vol. l, pp. 466–471 (2003)
3.
Jin, D., Hu, Z.: A study on image retrieval based on semantics. J. Wuhan Univ., 1255–1259 (2009)
4.
Wang, C., Yang, Y., Chen, S.F.: Algorithms of high-level semantic-based image retrieval. J. Softw., 1461–1469 (2004)
Metadata
Title
An Image Retrieval Algorithm Based on Semantic Self-Feedback Mechanism
Authors
Lang Pei
Jia Xu
Jinhua Cai
Copyright Year
2018
Book
Advances in Intelligent Systems and Interactive Applications

Print ISBN: 978-3-319-69095-7

Electronic ISBN: 978-3-319-69096-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-69096-4_41

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