A Lightweight Network for Ship Detection in SAR Images Based on Edge Feature Aware and Fusion
Recently, with the increasing adoption of synthetic aperture radar (SAR) ship detection methods on mobile platforms, the lightweighting of detection methods has become a research focus. Despite certain achievements, there are still several limitations: 1) Existing studies have mainly focused on redu...
Saved in:
| Main Authors: | Yuming Li, Jin Liu, Xingye Li, Xiliang Zhang, Zhongdai Wu, Bing Han |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10818772/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Confidence-Aware Ship Classification Using Contour Features in SAR Images
by: Al Adil Al Hinai, 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) -
DEPDet: A Cross-Spatial Multiscale Lightweight Network for Ship Detection of SAR Images in Complex Scenes
by: Jing Zhang, et al.
Published: (2024-01-01) -
A Combined CNN-LSTM Network for Ship Classification on SAR Images
by: Abdelmalek Toumi, et al.
Published: (2024-12-01) -
DGSP-YOLO: A Novel High-Precision Synthetic Aperture Radar (SAR) Ship Detection Model
by: Zhu Lejun, et al.
Published: (2024-01-01)