Computer Vision: Algorithms and Applications (Texts in Computer Science)
Computer Vision: Algorithms and Applications is an exceptionally authoritative and comprehensive textbook/reference that takes a scientific approach to the formulation of computer vision problems and the latest classical and deep learning models.
Computer Vision: Algorithms and Applications (Texts in Computer Science)
Numéro d'article: 36412489

Computer Vision: Algorithms and Applications (Texts in Computer Science)

Numéro d'article: 36412489

DJF 16107

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Computer Vision: Algorithms and Applications is an exceptionally authoritative and comprehensive textbook/reference that takes a scientific approach to the formulation of computer vision problems and the latest classical and deep learning models.
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Ce qui se démarque

Comprehensive Coverage
This edition presents a detailed exploration of computer vision algorithms and applications, catering to both beginners and seasoned professionals seeking to enhance their knowledge in cutting-edge technology.
Updated Content
Incorporating the latest advancements in the field, the second edition provides contemporary examples and practical applications, ensuring that readers stay informed about current trends and innovations in computer vision.
Accessible Learning
With clear explanations and structured chapters, this textbook effectively simplifies complex concepts, making it an invaluable resource for students and researchers alike, enhancing their understanding and practical skills in computer vision.

Détails du produit

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  • Explores techniques used to analyze and interpret images, with real-world applications and a scientific approach to problem formulation
  • Incorporates new material on deep learning and applications like mobile computational photography, autonomous navigation, and augmented reality
  • Features exercises at the end of each chapter with emphasis on testing algorithms and suggestions for projects
  • Includes 1,500 new citations and 200 new figures covering developments from the last decade
  • Provides additional material and detailed mathematical topics in the Appendices, covering linear algebra, numerical techniques, estimation theory, datasets, and software
  • Suitable for upper-level undergraduate or graduate-level courses in computer science or engineering, focusing on basic techniques that work under real-world conditions and current research literature
Publisher Springer
Publication date January 5, 2022
Edition Second Edition 2022
Language English
Print length 947 pages
ISBN-10 3030343715
ISBN-13 978-3030343712
Item Weight 7.6 ounces (215.46 grams)
Dimensions 8.56 x 1.67 x 11.1 inches (21.7 x 4.2 x 28.2 cm)
Part of series Texts in Computer Science

À qui est-ce destiné ?

Suitable For
  • Computer Science Students

    Ideal for those studying computer science, particularly in areas focusing on artificial intelligence and image processing.

  • Industry Professionals

    Beneficial for engineers and developers working in computer vision, providing algorithms and real-world applications.

  • Researchers

    Supports academic researchers looking for in-depth knowledge and contemporary developments in computer vision techniques.

Not Suitable For
  • Beginners

    Not suitable for those with no prior knowledge of computer vision or related programming skills.

DESCRIPTION DU PRODUIT

Computer Vision: Algorithms and Applications (Texts in Computer Science)

About This Item

Introducing the "Computer Vision: Algorithms and Applications" Texts in Computer Science 2nd ed. 2022 Edition. Unlock the power of computer vision and delve into the exciting realm of algorithms and applications with this comprehensive textbook. Designed for students and professionals alike, this updated edition is packed with cutting-edge information and practical examples to enhance your understanding of computer vision. With the rapid advancement of technology, computer vision has become increasingly relevant in various industries.

From autonomous vehicles to facial recognition systems, computer vision plays a crucial role in enabling machines to perceive and understand the visual world. This textbook covers a wide range of topics, including image formation, image filtering, feature detection and matching, segmentation, tracking, and more. It provides a solid foundation in the fundamental principles and techniques used in computer vision, allowing you to apply them to real-world scenarios. Whether you're a beginner or an experienced practitioner, this book is designed to cater to your needs. The clear and concise explanations, along with numerous illustrative figures, make complex concepts easier to grasp.

Additionally, the practical examples and exercises provided throughout the book will help you reinforce your knowledge and develop your skills. By studying "Computer Vision: Algorithms and Applications," you will gain insights into the latest advancements in this dynamic field. You'll learn how to design and implement computer vision algorithms, analyze visual data, and make informed decisions based on the extracted information. This edition also includes updated content to reflect the most current trends and technologies in computer vision. Stay up-to-date with the latest research and industry practices, ensuring you're equipped with the knowledge and skills needed to excel in this exciting field. With "Computer Vision: Algorithms and Applications" as your guide, you'll be well-prepared to tackle the challenges and opportunities that lie ahead in the world of computer vision.

Take the next step in your career or academic journey and add this essential resource to your library today.

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Intelligence & Semantics Editorial Review

Szeliski's book is an essential addition to the library of any computer vision practitioner. However, it is not suitable for those who are just starting as it functions more as a "survey paper" that covers all facets of the field. It glosses over much of the math and refers to other papers and texts for fundamental algorithms. That said, it has a valuable appendix section that references numerous software packages and sample data sets. The printing quality of the book is poor, and often the text from the next two pages shines through.

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Avantages

  • Essential addition for computer vision practitioners
  • Covers all aspects of Computer vision
  • Valuable appendix section with references to software packages and data sets

Les inconvénients

  • Not suitable for beginners as it glosses over much of the math

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