A Segmentation Framework for Acoustic Sidescan Sonar Images Using Improved Smallest Of Constant False Alarm Rate and MAP-MRF-Reference-Cited by-同舟云学术

A Segmentation Framework for Acoustic Sidescan Sonar Images Using Improved Smallest Of Constant False Alarm Rate and MAP-MRF

Published:2022-11-14 Issue: Volume: Page:
ISSN:
Container-title:The 16th International Conference on Underwater Networks & Systems
language:
Short-container-title:

Author:

Tang Yiteng¹^ORCID,Liu Jun²^ORCID,Song Shanshan¹^ORCID,Guan Wenxue¹^ORCID,Cui Jun-Hong³^ORCID

Affiliation:

1. College of Computer Science and Technology, Jilin University, CN

2. School of Electronic and Information Engineering, Beihang University, CN

3. College of Computer Science and Technology&Smart Ocean Science and Technology Research Institute, Jilin University, CN and Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3567600.3568140

Reference32 articles.

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2. Possibilistic fuzzy local information C-Means for sonar image segmentation

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4. A Deep Learning Approach to Target Recognition in Side-Scan Sonar Imagery

5. [ 5 ] J. Dunlop. Statistical modelling of sidescan sonar images. In Oceans ’97 . MTS/IEEE Conference Proceedings, volume 1 , pages 33– 38 vol. 1 , 1997 . [5] J. Dunlop. Statistical modelling of sidescan sonar images. In Oceans ’97. MTS/IEEE Conference Proceedings, volume 1, pages 33–38 vol.1, 1997.