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Authors: Leandro H. F. P. Silva 1 ; Jocival D. Dias Jr 1 ; Jean F. B. Santos 1 ; João F. Mari 2 ; Maurício C. Escarpinati 1 and André R. Backes 1

Affiliations: 1 School of Computer Science, Federal University of Uberlândia, Brazil ; 2 Federal University of Viçosa, Brazil

Keyword(s): Unmanned Aerial Vehicles, Precision Agriculture, Non-linear Distortion, Deep Learning.

Abstract: Unmanned Aerial Vehicles (UAV) have increasingly been used as tools in many tasks present in Precision Agriculture (PA). Due to the particular characteristics of the flight and the UAV equipment, several challenges need to be addressed, such as the presence of non-linear deformations in the captured images. These deformations impair the image registration process so they must be identified to be properly corrected. In this paper, we propose a Convolutional Neural Network (CNN) architecture to classify whether or not a given image has non-linear deformation. We compared our approach with 4 traditional CNNs and the results show that our model achieves has an accuracy similar to the compared CNNs, but with an extremely lower computational cost, which could enable its use in flight time, in a system embedded in the UAV.

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Paper citation in several formats:
Silva, L.; Dias Jr, J.; Santos, J.; Mari, J.; Escarpinati, M. and Backes, A. (2021). Non-linear Distortion Recognition in UAVs’ Images using Deep Learning. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 447-454. DOI: 10.5220/0010309504470454

@conference{visapp21,
author={Leandro H. F. P. Silva. and Jocival D. {Dias Jr}. and Jean F. B. Santos. and João F. Mari. and Maurício C. Escarpinati. and André R. Backes.},
title={Non-linear Distortion Recognition in UAVs’ Images using Deep Learning},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP},
year={2021},
pages={447-454},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010309504470454},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP
TI - Non-linear Distortion Recognition in UAVs’ Images using Deep Learning
SN - 978-989-758-488-6
IS - 2184-4321
AU - Silva, L.
AU - Dias Jr, J.
AU - Santos, J.
AU - Mari, J.
AU - Escarpinati, M.
AU - Backes, A.
PY - 2021
SP - 447
EP - 454
DO - 10.5220/0010309504470454
PB - SciTePress

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