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Detection of wheat height using optimized multi-scan mode of LiDAR during the entire growth stages.

, , , , , , , and . Comput. Electron. Agric., (2019)

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Improved Estimation of Leaf Chlorophyll Content from Non-Noon Reflectance Spectra of Wheat Canopies by Avoiding the Effect of Soil Background., , , , , , , and . Agro-Geoinformatics, page 1-4. IEEE, (2018)Use of an Active Canopy Sensor Mounted on an Unmanned Aerial Vehicle to Monitor the Growth and Nitrogen Status of Winter Wheat., , , , , , , , and . Remote. Sens., 12 (22): 3684 (2020)Improving wheat yield prediction integrating proximal sensing and weather data with machine learning., , , , , , , , , and . Comput. Electron. Agric., (2022)Optimizing rice in-season nitrogen topdressing by coupling experimental and modeling data with machine learning algorithms., , , , , , , , and . Comput. Electron. Agric., (June 2023)A newly developed method to extract the optimal hyperspectral feature for monitoring leaf biomass in wheat., , , , , , , , and . Comput. Electron. Agric., (2019)Predicting Rice Grain Yield Based on Dynamic Changes in Vegetation Indexes during Early to Mid-Growth Stages., , , , , , , , and . Remote. Sens., 11 (4): 387 (2019)A deep learning method for oriented and small wheat spike detection (OSWSDet) in UAV images., , , , , , , , , and . Comput. Electron. Agric., (2022)Detection of wheat height using optimized multi-scan mode of LiDAR during the entire growth stages., , , , , , , and . Comput. Electron. Agric., (2019)Early Detection of Powdery Mildew Disease and Accurate Quantification of Its Severity Using Hyperspectral Images in Wheat., , , , , , , , , and 1 other author(s). Remote. Sens., 13 (18): 3612 (2021)HISTIF: A New Spatiotemporal Image Fusion Method for High-Resolution Monitoring of Crops at the Subfield Level., , , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2020)