GitHub / HROlive / Tropical-Cyclone-Intensity-Estimation
Solution for categorizing hurricanes based on intensity, using a deep convolutional neural network architecture trained on GPUs. It was developed during the "NCC Portugal AI for Science Bootcamp" and it's mainly a recreation of the research paper titled "Tropical Cyclone Intensity Estimation Using a Deep Convolutional Neural Network".
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PURL: pkg:github/HROlive/Tropical-Cyclone-Intensity-Estimation
Stars: 8
Forks: 1
Open issues: 0
License: other
Language: Jupyter Notebook
Size: 27.6 MB
Dependencies parsed at: Pending
Created at: almost 3 years ago
Updated at: 8 months ago
Pushed at: almost 2 years ago
Last synced at: 3 months ago
Commit Stats
Commits: 14
Authors: 2
Mean commits per author: 7.0
Development Distribution Score: 0.214
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/HROlive/Tropical-Cyclone-Intensity-Estimation
Topics: cnn, convolutional-neural-networks, deep-learning, machine-learning, neural-network, python, tropical-cyclone, weather-forecast