doi:10.57967/hf/1743 license:mit region:us
---
license: mit
---

# Overview

This repository contains the trained weights and associated details for a YOLOv8s model fine-tuned to detect volcanic plumes and summit features of the Fuego Volcano in Guatemala. 
The dataset used for training can be found in the following Hugging Face dataset: [volcanic-plume](https://huggingface.co/datasets/edouard-rolland/volcanic-plumes)

# Citation

```
@inproceedings{rolland2024volcanic,

    author    = {Edouard G. A. Rolland and Kasper A. R. Grøntved and Anders Lyhne Christensen and Matthew Watson and Tom Richardson},

    title     = { Autonomous {UAV} Volcanic Plume Sampling Based on Machine Vision and Path Planning},

    year      = { 2024 },

    note      = {Under review},

}
```

# Acknowledgement

This work is supported by the WildDrone MSCA Doctoral Network funded by EU Horizon Europe under grant agreement no. 101071224, the Innovation Fund Denmark for the project DIREC (9142-00001B), and by the Engineering & Physical Sciences Research Council (UK) through the CASCADE (Complex Autonomous aircraft Systems Configuration, Analysis and Design Exploratory) programme grant (EP/R009953/1).


# Object detection classes

```
['plume', 'summit']
```

# Example of Predictions

The following <a href="https://www.youtube.com/watch?v=pSGYUPancfA">video</a> presents the model output for an entire flight.
More details can be found in the paper above on the model training and performance.

