BOEM and its partners are seeking to develop, automate, and enhance the detection and classification of important species in high-resolution aerial imagery by leveraging cutting-edge technologies, such as deep learning computer vision frameworks.

This study will develop detection and classification

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algorithms for protected species using artificial intelligence and machine learning.

These algorithms will be used to analyze aerial imagery collected in the Gulf of Mexico by the US Fish and Wildlife Service (USFWS) under a separate agreement.

This award will be a single-source cooperative agreement with a member institution of the Gulf Coast Cooperative Ecosystem Studies Units.Furthermore, BOEM is interested in developing a web-based visualization tool that will provide status updates on USFWS and BOEM remote-sensing, aerial-imagery surveys conducted in the Gulf of Mexico in areas where energy development is occurring or will occur.

This tool will be a valuable resource for stakeholders—including government agencies, researchers, and the public it will enable us to track the progress of ongoing surveys and access the latest data and information.Over the planned project timeline of five years, this study will develop the following:State-of-the-art detection and classification algorithms using artificial intelligence and machine learning to analyze aerial imagery gathered by the USFWS in the Gulf of MexicoA public-facing, web-based tool providing results of aerial surveys