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Vision / edited by Andrew Fabian, Janet Gibson, Mike Sheppard, Simone Weyand.
- Format:
- Book
- Series:
- Darwin College lectures.
- The Darwin College lectures
- Language:
- English
- Subjects (All):
- Vision.
- Physical Description:
- 1 online resource (xxiv, 204 pages) : digital, PDF file(s).
- Edition:
- 1st ed.
- Place of Publication:
- Cambridge : Cambridge University Press, 2021.
- Summary:
- Arising from the 2019 Darwin College Lectures, this book presents essays from seven prominent public intellectuals on the theme of vision. Each author examines this theme through the lens of their own particular area of expertise, making for a lively interdisciplinary volume including chapters on neuroscience, colour perception, biological evolution, astronomy, the future of technology, computer vision, and the visionary core of science. Featuring contributions by professors of neuroscience Paul Fletcher and Anya Hurlbert, professor of zoology Dan-Eric Nilsson, the futurist Sophie Hackford, Microsoft distinguished scientist Andrew Blake, theoretical physicist and author Carlo Rovelli, and Dr Carolin Crawford, the Public Astronomer at the University of Cambridge, this volume will be of interest to anybody curious about how we see the world.
- Contents:
- Cover
- Half-title
- Series information
- Title page
- Copyright information
- Dedication
- Contents
- List of Figures
- Notes on Contributors
- Acknowledgements
- Introduction
- 1 The Evolution of Eyes
- The Astonishing Diversity of Eyes
- How Did It All Start?
- What Happened after the First Opsin Evolved?
- A Problem of Photon Shortage Guides Evolution
- Ancient Alternative Solutions
- The Origin of Eyes
- Two Solutions to Imaging
- When Did the First Eye See the World?
- What Are Low-Resolution Eyes Used For?
- The Problem of Photon Shortage Returns: The Evolution of Lenses
- From Low to High Resolution and the Birth of a New Ecological System
- References
- 2 Visions
- Initial Caveat: Perception as a 'Controlled Hallucination'
- Perception as an Active Process
- Combining Sensory Input with Prior Expectations: Costs and Benefits
- Starting Ideas: Cybernetics, Models and Prediction
- Perception as Inference
- An Important Distinction: Sensation versus Perception
- Perception as Inference - the Importance of Prior Knowledge
- More on Prediction: A Key Process in Visual Processing
- Predictions at the Earliest Stages of Visual Processing - Removing the Predictable Signal
- Prediction within a Hierarchical System: Levels of Balance between Expectation and Input
- Summary: A System That Carries within It the Tendency to Create Visions
- Reconsidering Visions in the Context of a Hierarchy of Predictions
- Disturbing the Balance (i): A Change in Low-Level Sensory Input - Charles Bonnet Syndrome
- Disturbing the Balance (ii): A Shift in Expectations Producing a New Reality
- Disturbing the Balance (iii): A Pervasive Change in How Input and Expectation Are Integrated
- Conclusion
- 3 Colour and Vision
- What Is Colour?
- Colour Constancy.
- The Uncertainty of Vision: An Interpretive Process
- Individual Variations in Colour Constancy: #thedress
- The Fundamentals of Colour Vision
- Measuring Colour Constancy
- 4 Science, Vision, Perspective
- Visual Imagery in Science
- Science and Vision
- Perspective
- Perspective Has Two Separate Sides, a Bit in Tension with One Another
- Velocity Is Perspectival
- Elementary Particles Are Perspectival
- Gauge Theories
- Quantum Theory
- The Arrow of Time
- 5 Vision of the Cosmos
- Large-Aperture Telescopes
- Space Telescopes
- Interferometry
- X-Ray Astronomy
- Time-Domain Astronomy
- Gravitational-Wave Observation
- Cosmic-Ray Observation
- Neutrino Astronomy
- Further Reading
- 6 Visions of a Digital Future
- Machine Learning and Data Capture
- Sentient Avatars
- 7 Computer Vision
- Four Types of Machine That See
- Human Body Motion Capture
- Faces and Emotions
- Computer Vision in Medicine
- Driver Assistance and Autonomous Vehicles
- Three Principles for Vision
- Probabilistic Mechanisms
- Learning by Example and Big Data
- The Rise of Deep Networks
- Three Outstanding Challenges for Seeing Machines
- Adversarial Attacks
- Few-Shot Learning
- Safety-Critical Machines
- Index.
- Notes:
- Title from publisher's bibliographic system (viewed on 17 Sep 2021).
- ISBN:
- 1-108-94426-4
- 1-108-95049-3
- 1-108-94633-X
- OCLC:
- 1272902362
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