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".
This project helps meteorologists and climate scientists quickly and consistently categorize tropical cyclones by intensity. It takes satellite imagery of hurricanes as input and outputs a classification of their intensity, automating a task that traditionally requires significant manual effort and domain expertise. This tool is for professionals involved in hurricane monitoring and forecasting.
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Use this if you need a reliable, automated way to classify tropical cyclone intensity from satellite images, reducing human intervention and potential inconsistencies.
Not ideal if you need a real-time, production-ready system for live forecasting, as this is a research-oriented implementation.
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Sep 11, 2023
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