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57832100
Computer Vision: Principles, Algorithms, Applications, Learning
89% of respondents would recommend this to a friend
Item #:
57832100
MUR 4947
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This fully revised fifth edition is a comprehensive and up-to-date text suitable for undergraduate and graduate students, researchers and R&D engineers working in this vibrant subject.
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What Stands Out
Comprehensive Coverage
This edition offers an extensive look into computer vision principles and algorithms, ensuring readers gain a deep understanding of both foundational concepts and advanced applications.
Updated Algorithms
Incorporating the latest developments in the field, this book includes modern algorithms that enhance practical applications, making it ideal for researchers and practitioners alike.
Learning Focus
With a dedicated section on learning techniques, this edition bridges traditional methods with machine learning approaches, providing readers with robust tools for real-world problem solving.
Product Details
| Publisher | Academic Press |
| Publication date | November 29, 2017 |
| Edition | 5th |
| Language | English |
| Print length | 900 pages |
| ISBN-10 | 012809284X |
| ISBN-13 | 978-0128092842 |
| Item Weight | 4.41 pounds (2 kg) |
| Dimensions | 7.6 x 1.9 x 9.4 inches (19.3 x 4.8 x 23.9 cm) |
Who Should Buy?
-
Students in Academia
Ideal for university students studying computer science, artificial intelligence, or machine learning who need foundational knowledge in computer vision.
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Research Professionals
Useful for researchers in the field of image processing or computer vision looking for advanced algorithms and applications.
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Industry Practitioners
Beneficial for software engineers or data scientists working on real-world computer vision projects requiring practical implementation insights.
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Casual Learners
Not suitable for those with only a casual interest in computer vision who prefer general summaries over in-depth analysis.
Product Description
Computer Vision: Principles, Algorithms, Applications, Learning
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Computer Vision & Pattern Recognition Editorial Review
### Editorial Review The 5th Edition of "Computer Vision: Principles, Algorithms, Applications, Learning" by Davies has been met with enthusiastic reception from its readers, signifying its relevance in a rapidly evolving field. Despite being published in 2018, many reviewers appreciate its surprisingly up-to-date content that reflects the latest advancements in computer vision over the past decade. The textbook covers a broad spectrum of topics, well-organized into sections that cater to different levels of expertise: Low Level, Intermediate Level, and Advanced. This structured approach allows instructors the flexibility to choose relevant topics based on their curriculum needs. Advanced sections delve into both shallow and deep machine learning, including discussions on Vision and Motion, making it a comprehensive resource for those looking to deepen their understanding of current methodologies. Readers commend the clarity of Davies' writing. While the book keeps the mathematical complexity to a minimum—which some may find advantageous for beginners—it does strike a balance by including enough detail to ensure readers can grasp the underlying theories. Many appreciate the inclusion of practical applications drawn from Davies' extensive industry experience, which helps to contextualize the theoretical aspects of the content. As a reference book, users find it both informative and convenient, yet it also provides a solid foundation for self-study, particularly for those with a modest background in mathematics. Overall, the feedback suggests that "Computer Vision" is an enriching resource for both learners and educators in the field, striking an effective balance between accessibility and depth. ### Pros and Cons **
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Pros
- Up-to-date content relevant to recent advancements in computer vision.
- Comprehensive coverage with a structured organization of topics across different levels.
- Clear and accessible writing style, suitable for beginners.
- Balances theoretical understanding with practical applications.
- Excellent as both a reference book and self-study material.
Cons
- Mathematical content may be too minimal for some advanced courses.
Product Price History
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MUR 4947
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Features & Benefits
- Fully revised fifth edition covering the latest in computer vision.
- Suitable for undergraduate and graduate students, researchers, and R&D engineers.
- Includes three new chapters on Machine Learning.
- Practical demonstrations for real-world vision systems.
- Approachable mathematics and essential theory with well-illustrated examples.
- Recent developments sections keep readers updated with fast-moving trends.
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