Green Harvesting in Vineyard: A Deep Learning Empowered Methodology Under Low Budget Constraints

Green harvesting, also known as crop thinning, is a crucial practice in viticulture that aims to remove selected unripe grape clusters so that the remaining harvest can achieve better ripeness with less competition for resources. To help the automation of this process, we propose a Computer Visionassisted methodology for automatically positioning and counting growing grape clusters on either side of a vineyard row. Having a focus on small-medium enterprises (SMEs) winemakers, we developed our method to take into account the constraint of a low-budget output.

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Published
2024-09-26
DOI
https://doi.org/10.1109/cafe63183.2024.11069341
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
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article

Green Harvesting in Vineyard: A Deep Learning Empowered Methodology Under Low Budget Constraints

Claudio Tomazzoli, Antonino Parisi, Simone Scannapieco
Remote Sensing and LiDAR Applications
article

Green Harvesting in Vineyard: A Deep Learning Empowered Methodology Under Low Budget Constraints

Claudio Tomazzoli, Antonino Parisi, Simone Scannapieco
article en

Abstract

Green harvesting, also known as crop thinning, is a crucial practice in viticulture that aims to remove selected unripe grape clusters so that the remaining harvest can achieve better ripeness with less competition for resources. To help the automation of this process, we propose a Computer Visionassisted methodology for automatically positioning and counting growing grape clusters on either side of a vineyard row. Having a focus on small-medium enterprises (SMEs) winemakers, we developed our method to take into account the constraint of a low-budget output.

University of Verona (IT), University of Cagliari (IT)
Zero hunger
Openalex Percentile: Top 75%
Remote Sensing and LiDAR Applications
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Green Harvesting in Vineyard: A Deep Learning Empowered Methodology Under Low Budget Constraints — Claudio Tomazzoli, Antonino Parisi, et al. · (2024) | TGRS Research Map | TGRS