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  KEYWORD

Vine canopy detection within UAV based multispectral imagery

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, 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