The use of unmanned aerial vehicles (UAVs) in precision agriculture is gaining more and more interest. In this paper, we present a deep learning based method for estimating the crop and weed distribution from images captured by a UAV. The proposed approach runs on an embedded board equipped with a GPU. Quantitative experimental results have been obtained using real images from two different public datasets. The results demonstrate the effectiveness of the proposed approach. © Springer Nature Switzerland AG 2019.
Dettaglio pubblicazione
2019, Computer Analysis of Images and Patterns, Pages 100-108 (volume: 1089)
UAV image based crop and weed distribution estimation on embedded GPU boards (04b Atto di convegno in volume)
FAWAKHERJI MULHAM, Potena C., Bloisi D. D., Imperoli M., Pretto A., Nardi D.
ISBN: 978-3-030-29929-3; 978-3-030-29930-9
Gruppo di ricerca: Artificial Intelligence and Robotics
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