Robust & Explainable Seafloor AI

SeafloorAI, the first large AI-ready dataset for seafloor mapping using sonar imagery.

Abstract: Characterizing seafloor morphodynamics is essential for naval applications relying on extensive geoacoustic and environmental data over broad spatiotemporal scales. Understanding dynamics and uncertainty among numerous variables presents a significant out-of-distribution challenge, as AI/ML models often struggle with unseen distributions, leading to fragile predictions and unreliable explanations. To overcome these challenges, this project will develop new robust and explainable optimization methods using newly-curated seafloorAI datasets. The research outcomes—including an AI-ready multi-site seabed morphodynamic database, innovative trustworthy AI/ML optimization methods, and scalable implementations—will be linked to the Ocean Biogeographic Information System and Seabed 2030 to benefit a broad range of communities and stakeholders.