Making a Machine That Sees Like Us explains why and how our visual
perceptions can provide us with an accurate representation of the
external world. Along the way, it tells the story of a machine (a
computational model) built by the authors that solves the
computationally difficult problem of seeing the way humans do. This
accomplishment required a radical paradigm shift - one that
challenged preconceptions about visual perception and tested the
limits of human behavior-modeling for practical application.
The text balances scientific sophistication and compelling
storytelling, making it accessible to both technical and general
readers. Online demonstrations and references to the authors'
previously published papers detail how the machine was developed
and what drove the ideas needed to make it work. The authors
contextualize their new theory of shape perception by highlighting
criticisms and opposing theories, offering readers a fascinating
account not only of their revolutionary results, but of the
scientific process that guided the way.
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