Whitman richards (15 Ergebnisse)

Zustand: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Hardcover. Zustand: Very Good. pp.xix, 268p, many figures, a very good hardback (publisher's laminated boards), ex-library [0893912549].

Zustand: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Softcover. Zustand: Bon. Ancien livre de bibliothèque. Traces d'usure sur la couverture. Petite(s) trace(s) de pliure sur la couverture. Couverture légèrement déchirée. Salissures sur la tranche. Edition 1988. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisa ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Signs of wear on the cover. Slightly creased cover. Slightly torn cover. Stains on the edge. Edition 1988. Ammareal gives back up to 15% of this item's net price to charity organizations.…

Zustand: as new. Cambridge, MA: The MIT Press, 1988. Paperback. 480 pp.- Designed for the MIT course, Natural Computation, this extensive book of readings combines mathematics, artificial intelligence, computer science, experimental psychology, and neurophysiology in studying perception. Mathematics is emphasized for making perceptual inferences and the spectrum of mathematical techniques used is very broad. While the more than thirty readings focus primarily on vision, they also encompass the study of sound perception and the interpretation and application of forces including movement. Each article is a self contained example of how a perceptual problem may be tackled and solved. For example, what makes wood look like wood not like stone, sand, or grass? How can we represent three dimensional shapes when the same shape is rarely seen in exactly the same way? Each of the five sections is preceded by an introduction and the book concludes with problem sets. English text. Condition : as new. Condition : as new copy. ISBN 9780262680554. Keywords : , perception.…

Zustand: good. Prompt Shipment, shipped in Boxes, Tracking PROVIDEDGood, trade paperback book, sunned, 263 pages, 4to.

Zustand: New. In English.

Zustand: New. This 1996 book describes an exciting theoretical paradigm for visual perception based on experimental and computational insights. Editor(s): Knill, David C.; Richards, Whitman. Num Pages: 532 pages, 140 b/w illus. BIC Classification: JMM; JMRP; PSAN; UYQV. Category: (P) Professional & Vocational. Dimension: 254 x 178 x 27. Weight in Grams: 910. . 2008. 1st Edition. paperback. . . . . Books ship from the US and Ireland. …

Hardback. Zustand: 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.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 1996 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 modelling 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 others' work. Students and researchers in cognitive and visual science will find much to interest them in this thought-provoking collection.…

Zustand: 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.…

Zustand: New. In English.

Zustand: New. This 1996 book describes an exciting theoretical paradigm for visual perception based on experimental and computational insights. Editor(s): Knill, David C.; Richards, Whitman. Num Pages: 530 pages, 140 b/w illus. BIC Classification: JMM; JMRP; PSAN; UYQV. Category: (P) Professional & Vocational. Dimension: 247 x 174 x 29. Weight in Grams: 1163. . 1996. hardcover. . . . . Books ship from the US and Ireland. …

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 1996 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 modelling 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 others' work. Students and researchers in cognitive and visual science will find much to interest them in this thought-provoking collection.…