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Multi-phase Oil Tank Recognition for High Resolution Remote Sensing Images

Changjiang Liu1, Xuling Wu2, Bing Mo1, Yi Zhang3

1 School of Mathematics and Statistics, Key Lab of Enterprise Informationization and Internet of Things of Sichuan Province, Sichuan Province University Key Laboratory of Bridge Non-destruction Detecting and Engineering Computing, Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, China
2 School of Foreign Languages, Sichuan University of Science and Engineering, Zigong, China
3 College of Computer Science, Sichuan University, Chengdu, China

* Corresponding Author: Changjiang Liu, email

Intelligent Automation & Soft Computing 2018, 24(3), 671-678. https://doi.org/10.31209/2018.100000033

Abstract

With continuing commercialization of remote sensing satellites, the high resolution remote sensing image has been increasingly used in various fields of our life. However, processing technology of high resolution remote sensing images is still a tough problem. How to extract useful information from the massive information in high resolution remote sensing images is significant to the subsequent process. A multi-phase oil tank recognition of remote sensing images, namely coarse detection and artificial neural network (ANN) recognition, is proposed. The experimental results of algorithms presented in this paper show that the proposed processing technology is reliable and effective.

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Cite This Article

C. Liu, X. Wu, B. Mo and Y. Zhang, "Multi-phase oil tank recognition for high resolution remote sensing images," Intelligent Automation & Soft Computing, vol. 24, no.3, pp. 671–678, 2018.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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