Abstract
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.
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Fawakherji, M., Potena, C., Bloisi, D.D., Imperoli, M., Pretto, A., Nardi, D. (2019). UAV Image Based Crop and Weed Distribution Estimation on Embedded GPU Boards. In: Vento, M., et al. Computer Analysis of Images and Patterns. CAIP 2019. Communications in Computer and Information Science, vol 1089. Springer, Cham. https://doi.org/10.1007/978-3-030-29930-9_10
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DOI: https://doi.org/10.1007/978-3-030-29930-9_10
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