Description: 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 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
Price: 99.15 USD
Location: Gloucester
End Time: 2024-12-11T18:05:43.000Z
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Restocking Fee: No
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EAN: 9780262048972
UPC: 9780262048972
ISBN: 9780262048972
MPN: N/A
Book Title: Foundations of Computer Vision (Adaptive Computati
Number of Pages: 840 Pages
Language: English
Publication Name: Foundations of Computer Vision
Publisher: MIT Press
Subject: Engineering (General), Intelligence (Ai) & Semantics, Computer Vision & Pattern Recognition
Publication Year: 2024
Item Height: 1.4 in
Type: Textbook
Item Weight: 52.4 Oz
Subject Area: Computers, Technology & Engineering
Author: Phillip Isola, Antonio Torralba, William T. Freeman
Item Length: 9.3 in
Item Width: 8.3 in
Series: Adaptive Computation and Machine Learning Ser.
Format: Hardcover