Improving Up-Close Remote Sensing of Occluded Areas in Vineyards through Customized Multiple-Unmanned-Aerial-Vehicle Path Planning
Author:
Affiliation:
1. Information Technology Group, Wageningen University & Research, 6708 PB Wageningen, The Netherlands
2. Advanced Research and Technology Office, MathWorks, Natick, MA 01760, USA
Publisher
MDPI
Link
https://www.mdpi.com/2673-4931/29/1/57/pdf
Reference19 articles.
1. Mapping the Spatial Variability of Botrytis Bunch Rot Risk in Vineyards Using UAV Multispectral Imagery;Valente;Eur. J. Agron.,2023
2. Di, J., and Li, Q. (2022). A Method of Detecting Apple Leaf Diseases Based on Improved Convolutional Neural Network. PLoS ONE, 17.
3. Grape Detection, Segmentation and Tracking Using Deep Neural Networks and Three-Dimensional Association;Santos;Comput. Electron. Agric.,2020
4. Orchard Management with Small Unmanned Aerial Vehicles: A Survey of Sensing and Analysis Approaches;Zhang;Precis. Agric.,2021
5. Carbone, G., and Gomez-Bravo, F. (2015). Motion and Operation Planning of Robotic Systems: Background and Practical Approaches, Springer International Publishing.
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