Fully convolutional neural networks applied to large-scale marine morphology mapping

Fully convolutional neural networks applied to large-scale marine morphology mapping

In this study we applied for the first time Fully Convolutional Neural Networks (FCNNs) to a marine bathymetric dataset to derive morphological classes over the entire Irish continental shelf. FCNNs are a set of algorithms within Deep Learning that produce pixel-wise classifications in order to crea...

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Bibliographic Details
Main Authors: Riccardo Arosio, Brandon Hobley, Andrew J. Wheeler, Fabio Sacchetti, Luis A. Conti, Thomas Furey, Aaron Lim
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-07-01
Series:Frontiers in Marine Science
Subjects:
Fully Convolutional Neural Networks
marine
morphology
habitat mapping
bathymetry
Online Access:https://www.frontiersin.org/articles/10.3389/fmars.2023.1228867/full

Internet

https://www.frontiersin.org/articles/10.3389/fmars.2023.1228867/full

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