DEPDet: A Cross-Spatial Multiscale Lightweight Network for Ship Detection of SAR Images in Complex Scenes
Nowadays, the intricate nature of synthetic aperture radar (SAR) ship scenes, coupled with the presence of multiscale targets, poses a significant challenge in detection accuracy. Furthermore, to reduce the financial outlay on hardware, there is also a considerable challenge in lightweighting the mo...
Saved in:
Main Authors: | Jing Zhang, Fan Deng, Yonghua Wang, Jie Gong, Ziyang Liu, Wenjun Liu, Yinmei Zeng, Zeqiang Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10695810/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Lightweight Network for Ship Detection in SAR Images Based on Edge Feature Aware and Fusion
by: Yuming Li, et al.
Published: (2025-01-01) -
Multiscale Feature-Enhanced Water Body Detector of Truncated Gaussian Clutter in SAR Imagery
by: Bo Zhu, et al.
Published: (2025-01-01) -
LHSDNet: A Lightweight and High-Accuracy SAR Ship Object Detection Algorithm
by: Dahai Dai, et al.
Published: (2024-12-01) -
Low-dimensional multiscale fast SAR image registration method
by: Jiamu Li, et al.
Published: (2024-12-01) -
CERMF-Net: A SAR-Optical Feature Fusion for Cloud Elimination From Sentinel-2 Imagery Using Residual Multiscale Dilated Network
by: Jayakrishnan Anandakrishnan, et al.
Published: (2024-01-01)