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2024 Conference Publication From drones to satellites: biophysics-informed machine learning provides remote estimation of dynamic biomass across scalesChen, Qiaomin, Chen, Zhi, Hu, Pengcheng, Zheng, Bangyou, Smith, Daniel T.L., Fernandez, Javier, Garba, Ismail I. and Chapman, Scott C. (2024). From drones to satellites: biophysics-informed machine learning provides remote estimation of dynamic biomass across scales. 3rd International Wheat Congress, Perth, WA Australia, 22-27 September 2024. Perth, WA Australia: IWC. |
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2023 Conference Publication In-season phenotyping of wheat growth by integrating imaging, bio-physical modelling and machine learningChen, Q., Zheng, B., Chenu, K., Chen, T., Hu, P. and Chapman, S.C. (2023). In-season phenotyping of wheat growth by integrating imaging, bio-physical modelling and machine learning. Asia-Pacific Plant Phenomics Conference, Sanya, China, 7-10 July 2023. |
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2022 Conference Publication Improve wheat LAI estimation from high spatial resolution multispectral images via soil reflectance calibration and background correctionChen, Q., Zheng, B., Chenu, K., Hu, P. and Chapman, S. C. (2022). Improve wheat LAI estimation from high spatial resolution multispectral images via soil reflectance calibration and background correction. International Plant Phenotyping Symposium, Wageningen, Netherlands, 27-30 November 2022. |
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2022 Conference Publication Integrating APSIM and PROSAIL to improve prediction of crop traits in various situations from hyperspectral data using deep learningChen, Qiaomin, Zheng, Bangyou, Chen, Tong and Chapman, Scott (2022). Integrating APSIM and PROSAIL to improve prediction of crop traits in various situations from hyperspectral data using deep learning. 20th Agronomy Australia Conference, Toowoomba, QLD, Australia, 18-22 September 2022. Willow Grove, VIC Australia: Australian Society of Agronomy. |
