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Author: Gabriel Kreiman
Publisher: Cambridge University Press
ISBN: 1108483437
Category : Computers
Languages : en
Pages : 275
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Book Description
This book introduces neural mechanisms of biological vision and how artificial intelligence algorithms learn to interpret images.
Author: Gabriel Kreiman
Publisher: Cambridge University Press
ISBN: 1108483437
Category : Computers
Languages : en
Pages : 275
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Book Description
This book introduces neural mechanisms of biological vision and how artificial intelligence algorithms learn to interpret images.
Author: John P. Frisby
Publisher: MIT Press
ISBN: 0262514273
Category : Psychology
Languages : en
Pages : 577
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Book Description
An accessible yet rigorous and generously illustrated exploration of the computational approach to the study of biological vision. Seeing has puzzled scientists and philosophers for centuries and it continues to do so. This new edition of a classic text offers an accessible but rigorous introduction to the computational approach to understanding biological visual systems. The authors of Seeing, taking as their premise David Marr's statement that “to understand vision by studying only neurons is like trying to understand bird flight by studying only feathers,” make use of Marr's three different levels of analysis in the study of vision: the computational level, the algorithmic level, and the hardware implementation level. Each chapter applies this approach to a different topic in vision by examining the problems the visual system encounters in interpreting retinal images and the constraints available to solve these problems; the algorithms that can realize the solution; and the implementation of these algorithms in neurons. Seeing has been thoroughly updated for this edition and expanded to more than three times its original length. It is designed to lead the reader through the problems of vision, from the common (but mistaken) idea that seeing consists just of making pictures in the brain to the minutiae of how neurons collectively encode the visual features that underpin seeing. Although it assumes no prior knowledge of the field, some chapters present advanced material. This makes it the only textbook suitable for both undergraduate and graduate students that takes a consistently computational perspective, offering a firm conceptual basis for tackling the vast literature on vision. It covers a wide range of topics, including aftereffects, the retina, receptive fields, object recognition, brain maps, Bayesian perception, motion, color, and stereopsis. MatLab code is available on the book's website, which includes a simple demonstration of image convolution.
Author: John P. Frisby
Publisher: Oxford University Press, USA
ISBN:
Category : Medical
Languages : en
Pages : 170
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Book Description
Author: James Elder
Publisher: Frontiers Media SA
ISBN: 2832553451
Category : Science
Languages : en
Pages : 220
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Book Description
A principal challenge for both biological and machine vision systems is to integrate and organize the diversity of cues received from the environment into the coherent global representations we experience and require to make good decisions and take effective actions. Early psychological investigations date back more than 100 years to the seminal work of the Gestalt school. Yet in the last 50 years, neuroscientific and computational approaches to understanding perceptual organization have become equally important, and a full understanding requires integration of all three approaches. This highly interdisciplinary Research Topic welcomes contributions spanning Computer Science, Psychology, and Neuroscience, with the aim of presenting a single, unified collection that will encourage integration and cross-fertilization across disciplines.
Author: Erich Jantsch
Publisher: Routledge
ISBN: 1000301265
Category : Social Science
Languages : en
Pages : 244
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Book Description
"The evolutionary vision" is a term coined by economist Kenneth E. Boulding to describe a unified view of evolution that encompasses all levels of reality, from the cosmic or physical through the biological, ecological, and sociobiological to the sociocultural. It focuses less on systems or any particular entity than on the processes through which they evolve. In this volume various approaches to the self-organization of matter and information are outlined by authors who are among the chief developers of this new paradigm. They focus on the general laws governing evolutionary dynamics across all levels of evolution, including the evolution of humans and human systems.
Author: Samantha Fowler
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 1409
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Book Description
Concepts of Biology is designed for the typical introductory biology course for nonmajors, covering standard scope and sequence requirements. The text includes interesting applications and conveys the major themes of biology, with content that is meaningful and easy to understand. The book is designed to demonstrate biology concepts and to promote scientific literacy.
Author: Michael F. Land
Publisher: Oxford University Press
ISBN: 0199581134
Category : Science
Languages : en
Pages : 291
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Book Description
This book covers the way that all known types of eyes work, from their optics to the behaviour they guide. The ways that eyes sample the world in space and time are considered, and the evolutionary origins of eyes are discussed. This new edition incorporates discoveries made since the first edition published in 2001.
Author: Pomplun, Marc
Publisher: IGI Global
ISBN: 1466625406
Category : Computers
Languages : en
Pages : 447
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Book Description
"This book provides interdisciplinary research that evaluates the performance of machine visual models and systems in comparison to biological systems, blending the ideas of current scientific knowledge and biological vision"--
Author: Guy A. Orban
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 412
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Book Description
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309147867
Category : Science
Languages : en
Pages : 113
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Book Description
Now more than ever, biology has the potential to contribute practical solutions to many of the major challenges confronting the United States and the world. A New Biology for the 21st Century recommends that a "New Biology" approach-one that depends on greater integration within biology, and closer collaboration with physical, computational, and earth scientists, mathematicians and engineers-be used to find solutions to four key societal needs: sustainable food production, ecosystem restoration, optimized biofuel production, and improvement in human health. The approach calls for a coordinated effort to leverage resources across the federal, private, and academic sectors to help meet challenges and improve the return on life science research in general.
