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Deep Learning-Based Automatic Detection of Ships: An Experimental Study Using Satellite Images
Krishna Patel1, Chintan Bhatt2, Pier Luigi Mazzeo3
1Department of Computer Science & Engineering, Devang Patel Institute of Advance Technology and Research (DEPSTAR), CHARUSAT Campus, Charotar University of Science and Technology (CHARUSAT), Changa 388421, India.
This study demonstrates that YOLOv5 is the most accurate deep learning algorithm for automatic ship detection in satellite imagery, achieving 99% accuracy. This advancement aids maritime surveillance for security and environmental monitoring.
Area of Science:
- Remote Sensing
- Machine Learning
- Deep Learning
Background:
- Maritime surveillance is crucial for security and environmental protection.
- Automatic ship detection from satellite imagery is a key challenge with applications in traffic monitoring, illegal fishing prevention, and pollution control.
- Deep learning (DL) methods, particularly convolutional neural networks (CNNs), have shown significant promise in image recognition tasks.
Purpose of the Study:
- To develop and evaluate an automatic ship detection (ASD) approach using DL methods.
- To explore and compare different versions of the YOLO algorithm (YOLOv3, YOLOv4, YOLOv5) for ship detection in satellite images.
- To assess the performance of these algorithms on large satellite image datasets.
Main Methods:
- Utilized deep learning (DL) techniques for automatic ship detection (ASD).
- Compared YOLOv3, YOLOv4, and YOLOv5 algorithms for ship detection performance.
- Trained and evaluated algorithms on the Airbus Ship Challenge and Shipsnet datasets.
Main Results:
- All tested YOLO algorithms demonstrated effectiveness in detecting ships from satellite images.
- YOLOv5 achieved the highest accuracy at 99%.
- YOLOv4 and YOLOv3 achieved accuracies of 98% and 97%, respectively.
Conclusions:
- YOLOv5 is the superior algorithm for automatic ship detection among the evaluated YOLO versions.
- Deep learning approaches, specifically YOLOv5, offer a highly accurate solution for maritime surveillance using satellite imagery.
