Ship-Detection-on-Remote-Sensing-Synthetic-Aperture-Radar-Data and Trident-synthetic_aperture_radar_maritime_vessel_detection_yolov8

Both tools are competing solutions for maritime vessel detection in Synthetic Aperture Radar (SAR) data, with project A leveraging Faster-RCNN and YOLOv5 architectures and project B utilizing YOLOv8-OBB and Lee speckle filtering.

Ship-Detection-on-Remote-Sensing-Synthetic-Aperture-Radar-Data
39
Emerging
Trident-synthetic_aperture_radar_maritime_vessel_detection_yolov8
27
Experimental
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 13/25
Maintenance 6/25
Adoption 5/25
Maturity 9/25
Community 7/25
Stars: 144
Forks: 13
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 10
Forks: 1
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
No Package No Dependents

About Ship-Detection-on-Remote-Sensing-Synthetic-Aperture-Radar-Data

jasonmanesis/Ship-Detection-on-Remote-Sensing-Synthetic-Aperture-Radar-Data

Maritime vessel detection from remote sensing SAR data, based on the architectures of the Faster-RCNN and YOLOv5 networks.

About Trident-synthetic_aperture_radar_maritime_vessel_detection_yolov8

kbhujbal/Trident-synthetic_aperture_radar_maritime_vessel_detection_yolov8

📡 Production-grade maritime surveillance system for detecting ships in Synthetic Aperture Radar (SAR) imagery using YOLOv8-OBB (Oriented Bounding Boxes) and Lee speckle filtering. Handles the unique challenges of radar imagery: multiplicative noise and arbitrarily-oriented vessels.

Scores updated daily from GitHub, PyPI, and npm data. How scores work