Exploring deep learning techniques to detect and track tropical cyclones
Cyclones are the complex events characterized by strong winds surrounding a low-pressure area.
Intensity classification of cyclones is traditionally performed using Dvorak technique focusing on statistical relationships between different environmental parameters and the intensity.
This project aims to create an algorithm based on deep learning to recognize and classify tropical cyclones based on their intensities. We’ll utilize – a) Satellite imaging data b) BestTrack database information of tropical cyclones for the task.
The model will be developed for static (per satellite image) detection and classification and later extended to perform dynamic (continuous real-time) detection and classification while maintaining robustness.
Mentors
- Linus Magnusson
- Pedro Maciel
Participants
Ashwin Samudre