Visions of a generalized probability theory

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Evidential reasoning, rooted in the critique of classical Bayesian theory, offers a robust framework for modeling uncertainty and subjective beliefs. This book explores the intersection of computer vision and belief calculus, demonstrating how their integration can lead to significant advancements in both areas. It presents novel mathematical developments related to belief functions and proposes innovative solutions to fundamental challenges in computer vision, highlighting the potential for machines to gain human-like visual intelligence in complex environments.