--- 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 video presents the model output for an entire flight. More details can be found in the paper above on the model training and performance.