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Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods.

, , , , , , , , , , , , , , , , and . CoRR, (2020)

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The balance between spectral and spatial information to estimate straw cereal plant density at early growth stages from optical sensors., , , , and . Comput. Electron. Agric., (December 2023)Ultrahigh-resolution boreal forest canopy mapping: Combining UAV imagery and photogrammetric point clouds in a deep-learning-based approach., , , , , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2022)The impact of canopy structure assumption on the retrieval of GAI and Leaf Chlorophyll Content for wheat and maize crops., , , and . IGARSS, page 7216-7219. IEEE, (2019)Evaluation of the Methods for Estimating Leaf Chlorophyll Content with SPAD Chlorophyll Meters., , , , and . Remote. Sens., 14 (20): 5144 (2022)Global Wheat Head Dataset 2021: an update to improve the benchmarking wheat head localization with more diversity., , , , , , , , , and 25 other author(s). CoRR, (2021)Modeling the spatial distribution of plants on the row for wheat crops: Consequences on the green fraction at the canopy level., , , , , , and . Comput. Electron. Agric., (2017)Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods., , , , , , , , , and 7 other author(s). CoRR, (2020)