https://github.com/mallickboy/cyclone-intensity-and-track-prediction-using-deep-learning

My SERB Internship at IIIT Kalyani
https://github.com/mallickboy/cyclone-intensity-and-track-prediction-using-deep-learning

Last synced: 8 months ago
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My SERB Internship at IIIT Kalyani

• Host: GitHub
• URL: https://github.com/mallickboy/cyclone-intensity-and-track-prediction-using-deep-learning
• Owner: mallickboy
• Created: 2025-01-30T00:24:49.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2025-02-08T11:16:03.000Z (8 months ago)
• Last Synced: 2025-02-17T23:35:09.563Z (8 months ago)
• Size: 3.91 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Cyclone Intensity and Track Prediction using Deep Learning

**SERB-Funded Internship at IIIT Kalyani**

🚀 **Project Overview**  

This project focuses on **predicting cyclone intensity, track, wind speed, and central pressure** using **deep learning models**. Leveraging **INSAT-3D satellite data**, we analyze and forecast cyclone behavior over the **Bay of Bengal** with high accuracy.

📌 **Key Highlights**  

- Processed **80+ GB** of raw satellite data  

- Implemented **CNN-based deep learning models** for prediction  

- Achieved **99.6% accuracy** in central pressure estimation  

- Used **TensorFlow, YOLO, NumPy, Pandas, and Matplotlib**

📂 **Current Status**  

Due to the **large dataset size**, file restructuring and uploads are in progress. Stay tuned for updates!

🔗 **Project Guide & Institute**  

- Internship under **SERB-funded research at IIIT Kalyani**  

- Project Guide: [Add if required]

👨‍💻 **Tech Stack**  

- **Deep Learning:** TensorFlow, CNN, YOLO  

- **Data Processing:** NumPy, Pandas  

- **Visualization:** Matplotlib, Seaborn  

- **Deployment & Testing:** Google Colab, Jupyter Notebook

📜 **Future Work**  

- Fine-tuning models for **real-time cyclone tracking**  

- Integrating data from **multiple satellite sources**

📁 **Repository Contents**  

- `data/` → Processed datasets  

- `models/` → Trained deep learning models  

- `notebooks/` → Jupyter Notebooks with analysis  

- `results/` → Model predictions & visualizations

🚀 **Contributions & Contact**  

Feel free to open an **issue** or **pull request** if you'd like to contribute!  

Connect with me on GitHub: [mallickboy](https://github.com/mallickboy)