| KEYWORD |
Vine canopy detection within UAV based multispectral imagery
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, high-resolution aerial multispectral maps by Matrice 300 UAV and MAIA camera, together with many other sensors.
The aim of the Thesis is to develop and test new image processing methods to semantically interprets each pixel of the map, in an automatic way, to detect those representing the vine canopies.
See also 02_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