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A review of UAV platforms, sensors, and applications for monitoring of sugarcane crops
Remote Sensing Applications: Society and Environment,
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Integration of RGB-based vegetation index, crop surface model and object-based image analysis approach for sugarcane yield estimation using unmanned aerial vehicle
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2021
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Machine Learning Models to Estimate the Sugarcane Brix Values from Multitemporal Vegetation Indices
2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM),
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Evaluation of sum-NDVI values to estimate wheat grain yields using multi-temporal Landsat OLI data
Geocarto International,
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Pre-harvest Sugarcane Yield Estimation Using UAV-Based RGB Images and Ground Observation
Sugar Tech,
2018
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