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Ridge, J. T., Gray, P. C., Windle, A. E., & Johnston, D. W. (2020). Deep Learning for Coastal Resource Conservation: Automating Detection of Shellfish Reefs. Remote Sensing in Ecology and Conservation, 6, 431-440.
https://doi.org/10.1002/rse2.134

has been cited by the following article:

• TITLE: Utilizing Artificial Intelligence (AI) for the Identification and Management of Marine Protected Areas (MPAs): A Review

  AUTHORS: Şeyma Merve Kaymaz Mühling

  KEYWORDS: Marine Protected Areas, Artificial Intelligence, Automation, Decision-Making Tools

  JOURNAL NAME: Journal of Geoscience and Environment Protection, Vol.11 No.9, September 15, 2023

  ABSTRACT: The article discusses the application of artificial intelligence (AI) and automation in marine conservation, specifically in relation to the protection of marine ecosystems and the definition of marine protected areas (MPAs). It highlights the threats that marine ecosystems face due to human activities and emphasizes the importance of effective management and conservation efforts. By improving data gathering, processing, monitoring, and analysis, artificial intelligence, and automation, they can revolutionize marine research. In conclusion, this study emphasizes the importance of AI and automation in marine conservation responsibly and ethically. In order to integrate these technologies into decision-making processes, stakeholders and marine conservation professionals must collaborate. Through the use of artificial intelligence and automation, marine conservation efforts can be transformed by establishing new methods of collecting and analyzing data, making informed decisions, and managing marine ecosystems.