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Hyperspectral based study of vines diseases for agricolture 4.0 new decision support systems design

azienda Thesis in external company    


keywords AGRICOLTURE 4.0, ARTIFICIAL INTELLIGENCE, IMAGE PROCESSING, IMAGE SEGMENTATION, REMOTE SENSING, SMART AGRICULTURE, UAV, DRONES

Reference persons LORENZO COMBA

Thesis type SPERIMENTAL, SPERIMENTAL APPLIED

Description The proposed activity is in collaboration with DiSAFA (Department of Agricultural, Forest and Food Sciences) of UniTO, and it is within the framework of a research project NOVIAGRI (New applications Of Vegetation Indexes in AGRIculture) funded by EU FEASR. In 2021 and 2022, an extensive monitoring campaign has been conducted in two vineyards near Asti, collecting several dataset: in-field observations, spectral signature of hundreds of leaves (healthy and diseased) by handheld High Resolution Field Spectroradiometer, high-resolution aerial multispectral maps by Matrice 300 UAV and MAIA camera, together with many other sensors.
The aim of the Thesis is to process spectral data of several samples to automatically classify them in three category: health plants, “Flavescenza dorata” diseased and “Mal dell’esca” diseased plants. Results of the proposed activity will enable the development of new decision support system (DSS) for enhanced precision agriculture methodologies.

See also  03_noviagri.pdf  https://www.linkedin.com/company/laboratorio-di-meccatronica-universit%C3%A0-di-torino/

Required skills Mathworks Matlab


Deadline 08/07/2024      PROPONI LA TUA CANDIDATURA




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