Automated corrosion inspection is essential in the maritime industry, where continuous monitoring of ship hulls and docking infrastructure is necessary to ensure operational safety and structural reliability. However, many existing predictive and deep learning-based approaches depend heavily on large annotated datasets, extensive training procedures, and substantial computational resources, limiting their practicality in real-world and resource-constrained inspection environments. To address the
