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Automated evaluation of agricultural damage using UAV survey Cover

Automated evaluation of agricultural damage using UAV survey

Acta Universitatis Sapientiae, Agriculture and Environment
Volume 10 (2018): Issue 1 (December 2018)
By: Daniel Stojcsics,  Zsolt Domozi and  András Molnár  
Open Access
|Feb 2019

Authors

Daniel Stojcsics

stojcsics.daniel@nik.uni-obuda.hu

Institute of Applied Informatics, John von Neumann Faculty of Informatics, Óbuda University, Hungary

Zsolt Domozi

mr.zsolt.domozi@ieee.org

Institute of Applied Informatics, John von Neumann Faculty of Informatics, Óbuda University, Hungary

András Molnár

molnar.andras@nik.uni-obuda.hu

Institute of Applied Informatics, John von Neumann Faculty of Informatics, Óbuda University, Hungary
DOI: https://doi.org/10.2478/ausae-2018-0002 | Journal eISSN: 2068-2964
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Language: English
Page range: 20 - 30
Submitted on: Jan 20, 2018
|
Accepted on: Feb 28, 2018
|
Published on: Feb 23, 2019
Published by: Sapientia Hungarian University of Transylvania
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
deep learning,
convolutional neural network,
UAV,
Matlab,
survey,
precision agriculture,
game damage,
time series
Related subjects:
Chemistry,
Environmental chemistry,
Life sciences,
Plant science,
Ecology,
Life sciences, other

© 2019 Daniel Stojcsics, Zsolt Domozi, András Molnár, published by Sapientia Hungarian University of Transylvania
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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