Assessment of the Effectiveness of Spectral Indices Derived from EnMAP Hyperspectral Imageries Using Machine Learning and Deep Learning Models for Winter Wheat Yield Prediction
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Mucsi, L.; Litkey-Kovács, D.; Bonus, K.; Farmonov, N.; Elgendy, A.; Aji, L.; Sóti, M. Assessment of the Effectiveness of Spectral Indices Derived from EnMAP Hyperspectral Imageries Using Machine Learning and Deep Learning Models for Winter Wheat Yield Prediction. Remote Sens. 2025, 17, 3426. https://doi.org/10.3390/rs17203426
Mucsi L, Litkey-Kovács D, Bonus K, Farmonov N, Elgendy A, Aji L, Sóti M. Assessment of the Effectiveness of Spectral Indices Derived from EnMAP Hyperspectral Imageries Using Machine Learning and Deep Learning Models for Winter Wheat Yield Prediction. Remote Sensing. 2025; 17(20):3426. https://doi.org/10.3390/rs17203426
Chicago/Turabian StyleMucsi, László, Dorottya Litkey-Kovács, Krisztián Bonus, Nizom Farmonov, Ali Elgendy, Lutfi Aji, and Márkó Sóti. 2025. "Assessment of the Effectiveness of Spectral Indices Derived from EnMAP Hyperspectral Imageries Using Machine Learning and Deep Learning Models for Winter Wheat Yield Prediction" Remote Sensing 17, no. 20: 3426. https://doi.org/10.3390/rs17203426
APA StyleMucsi, L., Litkey-Kovács, D., Bonus, K., Farmonov, N., Elgendy, A., Aji, L., & Sóti, M. (2025). Assessment of the Effectiveness of Spectral Indices Derived from EnMAP Hyperspectral Imageries Using Machine Learning and Deep Learning Models for Winter Wheat Yield Prediction. Remote Sensing, 17(20), 3426. https://doi.org/10.3390/rs17203426