9780521461092 - Perception as Bayesian Inference Hardback de Knill; Richards (20 resultados)

Condición: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item for full refund. Ships via media mail.

Hardback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

hardcover. Condición: New. In shrink wrap. Looks like an interesting title!

Hardback. Condición: Very Good. Laminated boards, corners slightly bumped, owner's shelf mark on spine, some annotations in pen, binding tight. ; 7.5 X 1.25 X 10.5 inches; 530 pages.

Condición: Gut. Zustand: Gut | Seiten: 530 | Sprache: Englisch | Produktart: Bücher | 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.

Condición: New. In.

Condición: New.

Condición: New.

Condición: New.

Hardcover. Condición: new. Hardcover. 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. This book provides an introduction to and critical analysis of the Bayesian paradigm. Leading researchers in computer vision and experimental vision science describe general theoretical frameworks for modeling vision, detailed applications to specific problems and implications for experimental studies of human perception. The book provides a dialogue between different perspectives both within chapters, which draw on insights from experimental and computational work, and between chapters, through commentaries written by the contributors on each other's work. Students and researchers in cognitive and visual science will find much to interest them in this thought-provoking collection. Describes a new paradigm for building and testing theories of human visual perception based on Bayesian probability theory. Leading researchers in computer vision and experimental vision science describe theoretical frameworks, applications to specific problems, and implications for experimental studies. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condición: As New. Unread book in perfect condition.

Hardcover. Condición: Like New. Like New. book.

Condición: As New. Unread book in perfect condition.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Hardcover. Condición: Brand New. 516 pages. 10.50x7.50x1.25 inches. In Stock. This item is printed on demand.

Hardcover. Condición: new. Hardcover. 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. This book provides an introduction to and critical analysis of the Bayesian paradigm. Leading researchers in computer vision and experimental vision science describe general theoretical frameworks for modeling vision, detailed applications to specific problems and implications for experimental studies of human perception. The book provides a dialogue between different perspectives both within chapters, which draw on insights from experimental and computational work, and between chapters, through commentaries written by the contributors on each other's work. Students and researchers in cognitive and visual science will find much to interest them in this thought-provoking collection. Describes a new paradigm for building and testing theories of human visual perception based on Bayesian probability theory. Leading researchers in computer vision and experimental vision science describe theoretical frameworks, applications to specific problems, and implications for experimental studies. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This 1996 book describes an exciting paradigm for building and testing theories of human visual perception based on Bayesian probability theory. Leading researchers in computer vision and experimental vision science describe theoretical frameworks, applicat.

Hardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Buch. Condición: Neu. Perception as Bayesian Inference | David C. Knill (u. a.) | Buch | Gebunden | Englisch | 2011 | Cambridge University Press | EAN 9780521461092 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Hardcover. Condición: new. Hardcover. 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. This book provides an introduction to and critical analysis of the Bayesian paradigm. Leading researchers in computer vision and experimental vision science describe general theoretical frameworks for modeling vision, detailed applications to specific problems and implications for experimental studies of human perception. The book provides a dialogue between different perspectives both within chapters, which draw on insights from experimental and computational work, and between chapters, through commentaries written by the contributors on each other's work. Students and researchers in cognitive and visual science will find much to interest them in this thought-provoking collection. Describes a new paradigm for building and testing theories of human visual perception based on Bayesian probability theory. Leading researchers in computer vision and experimental vision science describe theoretical frameworks, applications to specific problems, and implications for experimental studies. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.