Article Versions Notes

Li K-Y, Burnside NG, Sampaio de Lima R, Villoslada Peciña M, Sepp K, Yang M-D, Raet J, Vain A, Selge A, Sepp K. The Application of an Unmanned Aerial System and Machine Learning Techniques for Red Clover-Grass Mixture Yield Estimation under Variety Performance Trials. Remote Sensing. 2021; 13(10):1994. https://doi.org/10.3390/rs13101994

Li, Kai-Yun, Niall G. Burnside, Raul Sampaio de Lima, Miguel Villoslada Peciña, Karli Sepp, Ming-Der Yang, Janar Raet, Ants Vain, Are Selge, and Kalev Sepp. 2021. "The Application of an Unmanned Aerial System and Machine Learning Techniques for Red Clover-Grass Mixture Yield Estimation under Variety Performance Trials" Remote Sensing 13, no. 10: 1994. https://doi.org/10.3390/rs13101994

Li, K.-Y., Burnside, N. G., Sampaio de Lima, R., Villoslada Peciña, M., Sepp, K., Yang, M.-D., Raet, J., Vain, A., Selge, A., & Sepp, K. (2021). The Application of an Unmanned Aerial System and Machine Learning Techniques for Red Clover-Grass Mixture Yield Estimation under Variety Performance Trials. Remote Sensing, 13(10), 1994. https://doi.org/10.3390/rs13101994