#chesapeakeconservancy — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #chesapeakeconservancy, aggregated by home.social.
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#ChesapeakeConservancy #datascience team developed an #AI #DeepLearning model for #mapping #wetlands, which resulted in 94% accuracy. This method for wetland mapping could deliver important outcomes for #protecting and #conserving wetlands. Kumar Mainali et al, Convolutional neural network for high-resolution wetland mapping with open data: Variable selection and the challenges of a generalizable model, Science of The Total Environment (2022). DOI:10.1016/j.scitotenv.2022.160622
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#ChesapeakeConservancy #datascience team developed an #AI #DeepLearning model for #mapping #wetlands, which resulted in 94% accuracy. This method for wetland mapping could deliver important outcomes for #protecting and #conserving wetlands. Kumar Mainali et al, Convolutional neural network for high-resolution wetland mapping with open data: Variable selection and the challenges of a generalizable model, Science of The Total Environment (2022). DOI:10.1016/j.scitotenv.2022.160622
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#ChesapeakeConservancy #datascience team developed an #AI #DeepLearning model for #mapping #wetlands, which resulted in 94% accuracy. This method for wetland mapping could deliver important outcomes for #protecting and #conserving wetlands. Kumar Mainali et al, Convolutional neural network for high-resolution wetland mapping with open data: Variable selection and the challenges of a generalizable model, Science of The Total Environment (2022). DOI:10.1016/j.scitotenv.2022.160622
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#ChesapeakeConservancy #datascience team developed an #AI #DeepLearning model for #mapping #wetlands, which resulted in 94% accuracy. This method for wetland mapping could deliver important outcomes for #protecting and #conserving wetlands. Kumar Mainali et al, Convolutional neural network for high-resolution wetland mapping with open data: Variable selection and the challenges of a generalizable model, Science of The Total Environment (2022). DOI:10.1016/j.scitotenv.2022.160622