Optimizing the learning of E3D models requires a multifaceted approach. One crucial aspect is identifying appropriate training datasets that accurately represent real-world scenarios. Furthermore, incorporating advanced training techniques such as optimization descent and regularization methods can significantly enhance the efficacy of E3D models.