Antonino Monti
Semi-Supervised Techniques for Solar Panel Segmentation in Aerial Images.
Rel. Paolo Garza, Edoardo Arnaudo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2022
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Abstract
There has been an ever-growing awareness in recent years about climate change, a phenomenon which is caused primarily by the massive use of fossil fuels by humans. One of the main solutions to this issue is to switch to low-carbon and renewable forms of energy, which include solar energy. To promote the use of photovoltaic panels, it is useful to have an extensive and updated database of installed panels and plants, which could help with performance evaluations, but the availability of such maps is scarce. A solution to this problem is to employ artificial intelligence systems that automatically detect panels in aerial images, specifically by detecting, segmenting and classifying every panel in a given image.
This is the objective of Instance Segmentation, one of the most frequently-tackled tasks in the field of Computer Vision
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