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license: mit |
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# Overview |
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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. |
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The dataset used for training can be found in the following Hugging Face dataset: [volcanic-plume](https://huggingface.co/datasets/edouard-rolland/volcanic-plumes) |
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# Citation |
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``` |
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@inproceedings{rolland2024volcanic, |
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author = {Edouard G. A. Rolland and Kasper A. R. Grøntved and Anders Lyhne Christensen and Matthew Watson and Tom Richardson}, |
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title = { Autonomous {UAV} Volcanic Plume Sampling Based on Machine Vision and Path Planning}, |
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year = { 2024 }, |
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note = {Under review}, |
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} |
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``` |
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# Acknowledgement |
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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). |
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# Object detection classes |
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``` |
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['plume', 'summit'] |
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``` |
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# Example of Predictions |
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The following <a href="https://www.youtube.com/watch?v=pSGYUPancfA">video</a> presents the model output for an entire flight. |
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More details can be found in the paper above on the model training and performance. |
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