Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 70.40.220.129

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

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

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic