The U-ReACH Model for Ship Detection over Satellite Imagery

This paper presents a new hybrid deep-learning model, U-ReACH, for detecting ships over satellite images. Specifically, the new U-ReACH model combines two well-known deep learning models, Unet and ResNet. However, applying a deep-learning model straight into satellite imagery-related tasks usually leads to poor performance due to data imbalance. An Auxiliary Classification Head is added at the end of the feature extraction stage to overcome the issue. Besides, a new loss function is used to handle the problem of imbalanced data. The experiment results were executed on the Airbus Ship dataset, including 192,556 satellite images, which showed the promise of the new approach.