To tackle these challenges, we propose a simple, yet effective model called Face Restoration and Relighting Network (FRR-Net). The FRR-Net architecture includes an encoder-decoder model with a ...

To enhance state representation, we employ an LSTM-based encoder-decoder model to capture essential patient history, ensuring robust decision-making. Experimental results on real-world datasets (MIMIC ...