LPFFNet: Lightweight Prior Feature Fusion Network for SAR Ship Detection
SAR ship detection is of great significance in marine safety, fisheries management, and maritime traffic. At present, many deep learning-based ship detection methods have improved the detection accuracy but also increased the complexity and computational cost. To address the issue, a lightweight pri...
Saved in:
| Main Authors: | Xiaozhen Ren, Peiyuan Zhou, Xiaqiong Fan, Chengguo Feng, Peng Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/10/1698 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Towards Efficient SAR Ship Detection: Multi-Level Feature Fusion and Lightweight Network Design
by: Wei Xu, et al.
Published: (2025-07-01) -
LSD-Det: A Lightweight Detector for Small Ship Targets in SAR Images
by: Zhen Wang, et al.
Published: (2025-01-01) -
Deformable Feature Fusion and Accurate Anchors Prediction for Lightweight SAR Ship Detector Based on Dynamic Hierarchical Model Pruning
by: Yue Guo, et al.
Published: (2025-01-01) -
BESW-YOLO: A Lightweight SAR Image Detection Model Based on YOLOv8n for Complex Scenarios
by: Xiao Tang, et al.
Published: (2025-01-01) -
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)