Detecting Underwater Concrete Cracks with Machine Learning: A Clear Vision of a Murky Problem

This paper presents the development of an underwater crack detection system for structural integrity assessment submerged structures, such as offshore oil and gas installations, pipelines, foundations bridges, dams, etc. Our focus is on use machine-learning-based approaches. First, a detailed literature review state current methods surface presented, highlighting challenges opportunities. An overview image augmentation approach creation optical effects also presented. Experimental results using standard network-based machine learning approach, which used in onshore environments, are A series test cases presented existing networks’ performance improved augmented images conditions. The effectiveness accuracy proposed detecting cracks concrete structures demonstrated. has potential to improve safety reliability prevent catastrophic failures.