7 citations as recorded by crossref.

1. Long-term prediction of Arctic sea ice concentrations using deep learning: Effects of surface temperature, radiation, and wind conditions Y. Kim et al. 10.1016/j.rse.2024.114568
2. A hybrid deep learning framework for improving short-term precipitation forecasts S. Salehi & S. Akbar Salehi Neyshabouri 10.1016/j.envsoft.2025.106635
3. Unveiling the Role of Weighted Loss Functions in Deep Learning-Based Nowcasting of Extreme Rainfall Events H. Choi et al. 10.1109/TGRS.2025.3592853
4. GA-SmaAt-GNet: Generative adversarial small attention GNet for extreme precipitation nowcasting E. Reulen et al. 10.1016/j.knosys.2024.112612
5. Rainfall Observation Leveraging Raindrop Sounds Acquired Using Waterproof Enclosure: Exploring Optimal Length of Sounds for Frequency Analysis S. Hwang et al. 10.3390/s24134281
6. Key factors for quantitative precipitation nowcasting using ground weather radar data based on deep learning D. Han et al. 10.5194/gmd-16-5895-2023
7. Advancing from historical precipitation reconstruction to real-time monitoring: Satellite-gauge fusion with near-real-time data gap-filling accounting for latency periods Z. Yun et al. 10.1016/j.jhydrol.2025.133913