Wang, X.; Zhang, J.; Xun, L.; Wang, J.; Wu, Z.; Henchiri, M.; Zhang, S.; Zhang, S.; Bai, Y.; Yang, S.;
et al. Evaluating the Effectiveness of Machine Learning and Deep Learning Models Combined Time-Series Satellite Data for Multiple Crop Types Classification over a Large-Scale Region. Remote Sens. 2022, 14, 2341.
https://doi.org/10.3390/rs14102341
AMA Style
Wang X, Zhang J, Xun L, Wang J, Wu Z, Henchiri M, Zhang S, Zhang S, Bai Y, Yang S,
et al. Evaluating the Effectiveness of Machine Learning and Deep Learning Models Combined Time-Series Satellite Data for Multiple Crop Types Classification over a Large-Scale Region. Remote Sensing. 2022; 14(10):2341.
https://doi.org/10.3390/rs14102341
Chicago/Turabian Style
Wang, Xue, Jiahua Zhang, Lan Xun, Jingwen Wang, Zhenjiang Wu, Malak Henchiri, Shichao Zhang, Sha Zhang, Yun Bai, Shanshan Yang,
and et al. 2022. "Evaluating the Effectiveness of Machine Learning and Deep Learning Models Combined Time-Series Satellite Data for Multiple Crop Types Classification over a Large-Scale Region" Remote Sensing 14, no. 10: 2341.
https://doi.org/10.3390/rs14102341
APA Style
Wang, X., Zhang, J., Xun, L., Wang, J., Wu, Z., Henchiri, M., Zhang, S., Zhang, S., Bai, Y., Yang, S., Li, S., & Yu, X.
(2022). Evaluating the Effectiveness of Machine Learning and Deep Learning Models Combined Time-Series Satellite Data for Multiple Crop Types Classification over a Large-Scale Region. Remote Sensing, 14(10), 2341.
https://doi.org/10.3390/rs14102341
