APA (7th ed.) Citation

Ahmed, A. A. M., Deo, R. C., Raj, N., Ghahramani, A., Feng, Q., Yin, Z., & Yang, L. (2021). Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data. Remote sensing (Basel, Switzerland), 13(4), 554. https://doi.org/10.3390/rs13040554

Chicago Style (17th ed.) Citation

Ahmed, A. A. Masrur, Ravinesh C. Deo, Nawin Raj, Afshin Ghahramani, Qi Feng, Zhenliang Yin, and Linshan Yang. "Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data." Remote Sensing (Basel, Switzerland) 13, no. 4 (2021): 554. https://doi.org/10.3390/rs13040554.

MLA (9th ed.) Citation

Ahmed, A. A. Masrur, et al. "Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data." Remote Sensing (Basel, Switzerland), vol. 13, no. 4, 2021, p. 554, https://doi.org/10.3390/rs13040554.