For instance, Yuille and Bülthoff [44] describe the Bayesian approach to perception in terms of faithful depiction: “We define vision as perceptual inference, the estimation of scene properties from an image or sequence of images . . . ther…44. Yuille, A., and Bülthoff, H. (1996). Bayesian decision theory and psychophysics, in Perception as Bayesian inference, ed. D. Knill and W. Richards (Cambridge University Press, Cambridge).
45. Zollman, K. (2005). Talking to neighbors: T…
Alan Yuille
scientist · 2 mentions across 1 reading
In this course
Alan Yuille is a computational vision researcher known for modeling perception as Bayesian inference, treating vision as the statistical estimation of scene properties from incomplete visual information. His work grounds the course's discussion of how machines and biological systems alike must resolve uncertainty through probabilistic reasoning, establishing a bridge between psychophysics and artificial perception that underpins contemporary machine learning approaches to vision.
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