Naval Mine Detection and Classification: A Comparative Analysis of Deep Learning and Machine Learning Techniques

A study on the use of deep learning and machine learning techniques for mine detection and classification. This research aims to automate the process of identifying and classifying rocks and mines using machine learning and computer vision techniques. The deep learning algorithm, YOLOv5 is trained with labelled datasets and is utilised for identification. With the use of SONAR measurements, the classification is carried out using machine learning techniques. The results of the study demonstrate the effectiveness of using machine learning and YOLOv5 for rock vs mine detection, providing a solution for efficient and accurate identification in real-time. This technology may find use in a number of industries, including mining, geology, and the military.