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In-field grape berries counting for yield estimation using dilated CNNs (1909.12083v1)
Published 26 Sep 2019 in cs.CV, cs.LG, eess.IV, and stat.ML
Abstract: Digital technologies ignited a revolution in the agrifood domain known as precision agriculture: a main question for enabling precision agriculture at scale is if accurate product quality control can be made available at minimal cost, leveraging existing technologies and agronomists' skills. As a contribution along this direction we demonstrate a tool for accurate fruit yield estimation from smartphone cameras, by adapting Deep Learning algorithms originally developed for crowd counting.