ORS-Net: A Ship Detector for SAR Image Based on Oriented R-CNN-Reference-Cited by-同舟云学术

ORS-Net: A Ship Detector for SAR Image Based on Oriented R-CNN

Published:2023-03-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 9th International Conference on Computing and Artificial Intelligence
language:
Short-container-title:

Author:

Liu Hongning¹^ORCID,Zhang Rubo¹^ORCID,Xie Mingjie²^ORCID,Feng Pengming³^ORCID,He Guangjun³^ORCID,Xu Guokai⁴^ORCID

Affiliation:

1. College of Mechanical and Electronic Engineering, Dalian Minzu University, China

2. College of Computer Science and Technology, Harbin Engineering University, China

3. State Key Laboratory of Space-Ground Integrated Information Technology, Space Star Technology Company Ltd., China

4. College of Mechanical Engineering, Zhuhai College of Science and Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3594315.3594325

Reference48 articles.

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2. Zhou D.; Zeng L.; Zhang K. A novel SAR target detection algorithm via multi-scale SIFT features. J. Northwest. Polytech. Univ. 2015 33 867–873. Zhou D.; Zeng L.; Zhang K. A novel SAR target detection algorithm via multi-scale SIFT features. J. Northwest. Polytech. Univ. 2015 33 867–873.

3. Ship detection in South African oceans using SAR, CFAR and a Haar-like feature classifier

4. Xu F.; Liu J.H. Ship detection and extraction using visual saliency and bar graph of oriented gradient. Optoelectron. Lett. 2016 12 473–477. Xu F.; Liu J.H. Ship detection and extraction using visual saliency and bar graph of oriented gradient. Optoelectron. Lett. 2016 12 473–477.

5. Building Detection from Terrestrial Images