Degradation Model

Degradation modeling focuses on mathematically representing the processes that corrupt data, such as image blurring or battery capacity loss, to improve data restoration or predictive maintenance. Current research emphasizes developing more realistic degradation models, often incorporating physics-based insights and employing machine learning techniques like deep neural networks, diffusion models, and Bayesian neural networks to capture complex degradation patterns. These advancements are crucial for improving the accuracy of image restoration, predictive maintenance of infrastructure, and the development of more robust and reliable systems across various applications.