2025
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BUSINESS TOOl

M24AS00417
Bureau of Ocean Energy Management
Opening date 31 Jul 2024, 12:00AM
Closing date 2 Sep 2024, 12:00AM
Funding Opportunity Number: M24AS00417
Opportunity Category: Discretionary
CFDA Number(s): 15.423 -- Bureau of Ocean Energy Management (BOEM) Environmental Studies (ES)
Cost Sharing or Matching Requirement: No
Posted Date: Jul 31, 2024 12:00:00 AM EDT
Closing Date: Sep 02, 2024 12:00:00 AM EDT
Closing Date Details: Electronically submitted applications must be submitted no later than 5:00 p.m., ET,on the listed application due date.
Estimated Total Program Funding: 350000
Award Ceiling: $350000
Award Floor: $300000
Eligible Applicants: Others (see text field entitled "Additional Information on Eligibility" for clarification)
Additional Information on Eligibility: Single Source Cooperative Agreement with the University of Florida
Agency Name: Bureau of Ocean Energy Management
Description: 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 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
Grantor Contact Information: Dominquie Bruce-Morton dominique.bruce-morton@bsee.gov
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