Detection of ocean internal waves based on Faster R-CNN in SAR images

Sude BAO; Junmin MENG; Lina SUN; Yongxin LIU

doi:10.1007/s00343-019-9028-6

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Detection of ocean internal waves based on Faster R-CNN in SAR images

Physics | Updated：2023-04-27

- Detection of ocean internal waves based on Faster R-CNN in SAR images
- Detection of ocean internal waves based on Faster R-CNN in SAR images
- 海洋湖沼学报（英文） 2020年38卷第1期页码：55-63
- Affiliations：
  
  1.Inner Mongolia University, Hohhot 010021, China
  2.First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
- Author bio：
  
  MENG Junmin, mengjm@fio.org.cn
- Funds：
  
  the National Natural Science Foundation of China(61471136);the Special Project for Global Change and Air-sea Interaction of Ministry of Natural Resources(GASI-02-SCS-YGST2-04);the Chinese Association of Ocean Mineral Resources R & D(DY135-E2-4);© Chinese Society for Oceanology and Limnology, Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020
- DOI：10.1007/s00343-019-9028-6
  中图分类号：
- 收稿：2019-02-19，
  
  录用：2019-4-8，
  
  网络首发：2019-04-26，
  
  纸质出版：2020-01
- Accepted：
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Detection of ocean internal waves based on Faster R-CNN in SAR images[J]. 海洋湖沼学报（英文）, 2020,38(1):55-63.

Sude BAO, Junmin MENG, Lina SUN, et al. Detection of ocean internal waves based on Faster R-CNN in SAR images[J]. Journal of Oceanology and Limnology, 2020, 38(1): 55-63.
Detection of ocean internal waves based on Faster R-CNN in SAR images[J]. 海洋湖沼学报（英文）, 2020,38(1):55-63. DOI： 10.1007/s00343-019-9028-6.

Sude BAO, Junmin MENG, Lina SUN, et al. Detection of ocean internal waves based on Faster R-CNN in SAR images[J]. Journal of Oceanology and Limnology, 2020, 38(1): 55-63. DOI： 10.1007/s00343-019-9028-6.

摘要

Abstract

Ocean internal waves appear as irregular bright and dark stripes on synthetic aperture radar (SAR) remote sensing images. Ocean internal waves detection in SAR images consequently constituted a difficult and popular research topic. In this paper

ocean internal waves are detected in SAR images by employing the faster regions with convolutional neural network features (Faster R-CNN) framework; for this purpose

888 internal wave samples are utilized to train the convolutional network and identify internal waves. The experimental results demonstrate a 94.78% recognition rate for internal waves

and the average detection speed is 0.22 s/image. In addition

the detection results of internal wave samples under different conditions are analyzed. This paper lays a foundation for detecting ocean internal waves using convolutional neural networks.

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references

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