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TCDetect: A New Method of Detecting the Presence of Tropical Cyclones Using Deep Learning

This repo contains the code used to produce the results in the paper "TCDetect: A New Method of Detecting the Presence of Tropical Cyclones Using Deep Learning" published by AMS's Artificial Intelligence for the Earth Systems at https://journals.ametsoc.org/view/journals/aies/2/3/AIES-D-22-0045.1.xml. Please feel free to use this to confirm the results in the manuscript and you can reach out to me at galea.daniel18@gmail.com if you have any questions.

The code and data is available on Zenodo at https://zenodo.org/records/6595071 and can be cited as "Daniel Galea, Julian Kunkel, & Bryan N. Lawrence. (2022). TCDetect: A new method of Detecting the Presence of Tropical Cyclones using Deep Learning. Zenodo. https://doi.org/10.5281/zenodo.6595071" with a DOI of 10.5281/zenodo.6595071.

The code is available under the CC-BY 4 license.

This work was funded by Natural Environment Research Council (NERC) as part of the U.K. Government Department for Business, Energy and Industrial Strategy (BEIS) National Productivity Investment Fund (NPIF), Grant NE/R008868/1 under the SCENARIO Doctoral Training Partnership hosted by the University of Reading.

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