Deep Learning In Image Processing And Scientific Computing

This article discusses the recent advancements in deep learning and its impact on various industries and domains. It highlights the success of deep learning models and the factors contributing to it, such as large-scale datasets, computing power, and model architectures. The article also mentions ongoing research areas in deep learning, including theoretical understanding, interpretability, robustness, and training efficiency. The Special Issue aims to showcase cutting-edge advancements in deep learning and invites submissions on topics such as generalizability and robustness of models.