Ship Detection in Complex Environment Using SAR Time Series
Ship detection in complex environment is a challenging task due to strong background inferences, for which various deep-learning-based methods have been proposed. However, they have poor performance on detecting nearshore ships for medium-resolution synthetic aperture radar (SAR) images due to the l...
Main Authors: | Shakila Kahar, Fengming Hu, Feng Xu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9763320/ |
Similar Items
-
D-MFPN: A Doppler Feature Matrix Fused with a Multilayer Feature Pyramid Network for SAR Ship Detection
by: Yucheng Zhou, et al.
Published: (2023-01-01) -
A Ship Detection Method via Redesigned FCOS in Large-Scale SAR Images
by: Mingming Zhu, et al.
Published: (2022-02-01) -
A Novel Anchor-Free Method Based on FCOS + ATSS for Ship Detection in SAR Images
by: Mingming Zhu, et al.
Published: (2022-04-01) -
LssDet: A Lightweight Deep Learning Detector for SAR Ship Detection in High-Resolution SAR Images
by: Guoxu Yan, et al.
Published: (2022-10-01) -
Monitoring of Construction Activity by Change Detection on SAR Time Series Using Coherent Scatterers
by: Carlos Villamil Lopez, et al.
Published: (2022-01-01)