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Detalles bibliogr�ficos

T�tulo

Perception as Bayesian Inference

Editor

Cambridge University Press

Fecha de publicaci�n

1996

Idioma

Ingl�s

ISBN 10

052146109X

ISBN 13

9780521461092

Encuadernaci�n

Encuadernaci�n de tapa dura

Estado

good

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Sinopsis

This 1996 book describes an exciting theoretical paradigm for visual perception based on experimental and computational insights.

De la contraportada

In recent years, Bayesian probability theory has emerged not only as a powerful tool for building computational theories of vision, but also as a general paradigm for studying human visual perception. The Bayesian approach provides new and powerful metaphors for conceptualizing visual perception, suggests novel questions to ask about perceptual processing, and provides the means to formalize theories of perception that make testable predictions about human perceptual performance. This book provides an introduction to and critical analysis of the Bayesian paradigm. Chapters by leading researchers in computational theory and experimental visual science introduce new theoretical frameworks for building perceptual theories, discuss the implications of the Bayesian paradigm for psychophysical studies of human perception, and describe specific applications of the approach. The editors have created a critical dialogue of ideas through the authors' commentaries on each others' chapters, conveying to the reader a unique appreciation for the issues and ideas raised in the book.

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