Perception Error

Perception error, the discrepancy between perceived and actual reality, is a critical area of research impacting diverse fields from autonomous driving to medical diagnosis. Current research focuses on developing models, including deep neural networks and probabilistic programs, to detect and correct these errors, often integrating human expertise through collaborative systems or user feedback in virtual environments. This work is crucial for improving the safety and reliability of autonomous systems, enhancing diagnostic accuracy in healthcare, and advancing our understanding of human perception itself. The ultimate goal is to build more robust and trustworthy systems that account for and mitigate the inherent limitations of perception.