DGSP-YOLO: A Novel High-Precision Synthetic Aperture Radar (SAR) Ship Detection Model
With the rapid advancement of deep learning, its application in synthetic aperture radar (SAR) ship target detection has become increasingly prevalent. However, the detection of ships in complex environments and across various scales remains a formidable challenge. This paper introduces DGSP-YOLO, a...
Saved in:
| Main Authors: | Zhu Lejun, Chen Jingliang, Chen Jiayu, Yang Hao |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10752533/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Guest Editorial: Synthetic aperture in sonar and radar
by: Marco Martorella, et al.
Published: (2024-11-01) -
Ship detection using ensemble deep learning techniques from synthetic aperture radar imagery
by: Himanshu Gupta, et al.
Published: (2024-11-01) -
Remote sensing of the Earth by synthetic aperture radar
by: A.N. Leukhin, et al.
Published: (2018-03-01) -
LH-YOLO: A Lightweight and High-Precision SAR Ship Detection Model Based on the Improved YOLOv8n
by: Qi Cao, et al.
Published: (2024-11-01) -
Dual-Modal Approach for Ship Detection: Fusing Synthetic Aperture Radar and Optical Satellite Imagery
by: Mahmoud Ahmed, et al.
Published: (2025-01-01)