Proceedings of the International Symposium on Mechanical Engineering and Material Science

Coastline Identification from Remote-sensing Image Using Informative Vector Machine Learning

Authors
Guoshao Su, Xiaochun Hu, Liubin Yan, Yanming Liu
Corresponding Author
Guoshao Su
Available Online December 2016.
DOI
10.2991/ismems-16.2016.48How to use a DOI?
Keywords
Machine learning, Informative vector machine, Coastline identification
Abstract

For a more rapid and accurate coastline identification method, this paper presents a method of coastline identification on remote-sensing image using Informative Vector Machine and then the coastline of Beihai Silver Beach in Guangxi has been identified. The results show that method of coastline identification on remote-sensing using Informative Vector Machine avoids the accuracy deficiency of the edge detection and threshold segmentation, and overcomes a series of open problems that difficulty in determining the optimal network topology structure in artificial neural network and the hyper-parameters in Support Vector Machine. The quick and accurate identification of coastline using the method has been realized which provides an efficient mean for the identification and monitoring of coastline

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the International Symposium on Mechanical Engineering and Material Science
Series
Advances in Engineering Research
Publication Date
December 2016
ISBN
10.2991/ismems-16.2016.48
ISSN
2352-5401
DOI
10.2991/ismems-16.2016.48How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Guoshao Su
AU  - Xiaochun Hu
AU  - Liubin Yan
AU  - Yanming Liu
PY  - 2016/12
DA  - 2016/12
TI  - Coastline Identification from Remote-sensing Image Using Informative Vector Machine Learning
BT  - Proceedings of the International Symposium on Mechanical Engineering and Material Science
PB  - Atlantis Press
SP  - 283
EP  - 287
SN  - 2352-5401
UR  - https://doi.org/10.2991/ismems-16.2016.48
DO  - 10.2991/ismems-16.2016.48
ID  - Su2016/12
ER  -