About this product

Product Identifiers

PublisherMIT Press

ISBN-100262048973

ISBN-139780262048972

eBay Product ID (ePID)12060716261

Product Key Features

Number of Pages840 Pages

Publication NameFoundations of Computer Vision

LanguageEnglish

Publication Year2024

SubjectEngineering (General), Intelligence (Ai) & Semantics, Computer Vision & Pattern Recognition

TypeTextbook

Subject AreaComputers, Technology & Engineering

AuthorPhillip Isola, Antonio Torralba, William T. Freeman

SeriesAdaptive Computation and Machine Learning Ser.

FormatHardcover

Dimensions

Item Height1.3 in

Item Weight55.5 Oz

Item Length9.3 in

Item Width8.2 in

Additional Product Features

Intended AudienceTrade

LCCN2023-024588

Dewey Edition23

IllustratedYes

Dewey Decimal006.37

SynopsisFoundations of Computer Vision comprehensively introduces the foundations of the field while incorporating the latest deep learning advances, it takes a holistic approach that goes beyond machine learning and addresses fundamental issues in the task of vision and the relationship of machine vision to human perception. Written by leaders in the field and honed by a decade of classroom experience, this authoritative and highly teachable book offers an essential next-generation view of computer vision. Integrates classic computer vision and deep learning, Emphasizes fundamentals and assumes little background knowledge, Includes coverage of transformers, diffusion models, statistical image models, issues of fairness and ethics, and the research process, Features extensive examples and instructor resources, An accessible, authoritative, and up-to-date computer vision textbook offering a comprehensive introduction to the foundations of the field that incorporates the latest deep learning advances. Machine learning has revolutionized computer vision, but the methods of today have deep roots in the history of the field. Providing a much-needed modern treatment, this accessible and up-to-date textbook comprehensively introduces the foundations of computer vision while incorporating the latest deep learning advances. Taking a holistic approach that goes beyond machine learning, it addresses fundamental issues in the task of vision and the relationship of machine vision to human perception. Foundations of Computer Vision covers topics not standard in other texts, including transformers, diffusion models, statistical image models, issues of fairness and ethics, and the research process. To emphasize intuitive learning, concepts are presented in short, lucid chapters alongside extensive illustrations, questions, and examples. Written by leaders in the field and honed by a decade of classroom experience, this engaging and highly teachable book offers an essential next-generation view of computer vision. Up-to-date treatment integrates classic computer vision and deep learning Accessible approach emphasizes fundamentals and assumes little background knowledge Student-friendly presentation features extensive examples and images Proven in the classroom Instructor resources include slides, solutions, and source code

LC Classification NumberTA1634.T66 2024