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Item #:
6577566
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information (Mit Press)
85% of respondents would recommend this to a friend
Item #:
6577566
USD 61
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What Stands Out
Cutting-Edge Research
Offers groundbreaking insights into how humans perceive and process visual stimuli, ideal for researchers and students in cognitive science and psychology.
Interdisciplinary Approach
Integrates theories from neuroscience, psychology, and artificial intelligence, providing a comprehensive understanding of visual information processing.
Practical Applications
Equips readers with knowledge applicable in various fields, including education, design, and technology, enhancing their ability to analyze visual communication.
Product Details
| Publisher | The MIT Press |
| Publication date | July 9, 2010 |
| Language | English |
| Print length | 428 pages |
| ISBN-10 | 0262514621 |
| ISBN-13 | 978-0262514620 |
| Item Weight | 1.54 pounds (700 grams) |
| Dimensions | 7 x 0.72 x 9 inches (17.8 x 1.8 x 22.9 cm) |
Who Should Buy?
-
Cognitive Scientists
Ideal for researchers studying human cognition and visual perception, offering insights into computational models of visual information processing.
-
Students in AI
Beneficial for students focusing on artificial intelligence, as it explores the intersection of AI and human visual understanding.
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Psychology Professionals
Useful for psychologists interested in the mechanisms of visual perception and representation in the human brain.
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General Readers
Not suitable for casual readers as it requires a strong background in cognitive science or computational theory.
Product Description
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information (Mit Press)
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Neuroscience Editorial Review
The book "Vision: A Computational Investigation into the Human Representation and Processing of Visual Information" presents a revolutionary approach to studying vision. It argues that any explanation of vision has to account for three levels of understanding: computational theory, representation and algorithms, and hardware implementation. The technical content of the book is challenging, but it presents a beautiful hybrid view of how human and computer vision can be mutually beneficial. The book remains relevant today and is recommended to anyone interested in visual perception. However, it is missing key ideas such as attention, natural scene statistics, and learning. Readers with a fair amount of math/electrical engineering/algorithms experience will get much more out of the book.
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Pros
- Revolutionary approach to studying vision
- Presents a beautiful hybrid view of how human and computer vision can be mutually beneficial
- Recommended to anyone interested in visual perception
Cons
- Missing key ideas such as attention, natural scene statistics, and learning
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