Online Error

Online error detection and correction is a rapidly developing field focusing on identifying and mitigating errors in real-time across diverse applications, from procedural activity monitoring in videos to improving the accuracy of weather prediction models. Current research emphasizes the development of online one-class classifiers, neural network-based hybrid models, and algorithms that leverage symbolic reasoning or state machine extraction to enhance error detection accuracy and speed. These advancements have significant implications for improving the reliability and performance of various systems, ranging from autonomous vehicles and cyber-physical systems to complex scientific simulations.