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Jimenez, A
Psiroukis, V
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Authors
Oliveira, M.F
Morata, G.T
Ortiz, B
Silva, R.P
Jimenez, A
Psiroukis, V
Fountas, S
Uyar, H
Balafoutis, A
Kasimati, A
Topics
Big Data, Data Mining and Deep Learning
Drone Spraying
Type
Poster
Oral
Year
2022
2024
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1. Coupling Machine Learning Algorithms and GIS for Crop Yield Predictions Based on Remote Sensing Imagery and Topographic Indices

In-season yield prediction can support crop management decisions helping farmers achieve their yield goals. The use of remote sensing to predict yield it is an alternative for non-destructive yield assessment but coupling auxiliary data such as topography features could help increase the accuracy of yield estimation. Predictive algorithms that can effectively identify, process and predict yield at field scale base on remote sensing and topography still needed. Machine learning could be an alternative... M.F. Oliveira, G.T. Morata, B. Ortiz, R.P. Silva, A. Jimenez

2. Optimizing Vineyard Crop Protection: an In-depth Study of Spraying Drone Operational Parameters

In modern agriculture, the precise and efficient application of agrochemicals is essential to ensure crop health and increase productivity while minimizing adverse environmental impacts. While traditional spraying methods have long been the cornerstone of crop protection, the introduction of unmanned aerial vehicles (UAVs), commonly known as drones), has led to a revolutionary era in agriculture. UAVs offer novel opportunities to improve agricultural practices by providing precision, efficiency,... V. Psiroukis, S. Fountas, H. Uyar, A. Balafoutis, A. Kasimati