This example demonstrates how to extract useful information from satellite images using a simple deep learning based ship detector.
https://github.com/ppotoc/Detection-of-ships-on-satellite-images-using-YOLO-v2-deep-learning
You are now following this Submission
- You will see updates in your followed content feed
- You may receive emails, depending on your communication preferences
Detection of ships on satellite images using YOLO v2 deep learning
This MATLAB example demonstrates how to extract useful information from satellite images using a simple deep learning based ship detector, which can be included in a broad range of situational awareness sensors of maritime autonomous surface ships.
-
Download MATLAB LiveScript "YOLO_ship_detector.mlx" and data "data.zip"
-
Download MATLAB Add-On with a pretrained Deep Learning Toolbox Model for ResNet-50 Network https://www.mathworks.com/matlabcentral/fileexchange/64626-deep-learning-toolbox-model-for-resnet-50-network
-
Unzip "data.zip" containing train and test images, and image labelling session data
-
Run "YOLO_ship_detector.mlx" (change LiveScript parameter "doTraining" to train the model)
Cite As
Primoz Potocnik (2026). Detection of ships on satellite images using YOLO v2 (https://github.com/ppotoc/Detection-of-ships-on-satellite-images-using-YOLO-v2-deep-learning/releases/tag/v1.0.0), GitHub. Retrieved .
Acknowledgements
Inspired by: Object Detection Using YOLO v2 Deep-Learning
General Information
- Version 1.0.0 (25.6 MB)
-
View License on GitHub
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0 |
