Sonar Data

Sonar data analysis focuses on extracting meaningful information from acoustic images for underwater applications, primarily addressing challenges like low visibility and data scarcity. Current research emphasizes developing robust feature detection methods for automated object recognition and improved bathymetry estimation, often employing convolutional neural networks (CNNs), transformers, and self-supervised learning techniques to overcome limitations of traditional computer vision approaches and limited labeled datasets. These advancements are crucial for improving autonomous navigation, underwater mapping, and object detection in various sectors, including scientific exploration, defense, and environmental monitoring.