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This volume has its already distant or1g1n in an inter national conference on Evolutionary Epistemology the editors organized at the University of Ghent in November 1984. This conference aimed to follow up the endeavor started at the ERISS (Epistemologically Relevant Internalist Sociology of Science) conference organized by Don Campbell and Alex Rosen berg at Cazenovia Lake, New York, in June 1981, whilst in jecting the gist of certain current continental intellectual developments into a debate whose focus, we thought, was in danger of being narrowed too much, considering the still underdeveloped state of affairs in the field. Broadly speaking, evolutionary epistemology today con sists of two interrelated, yet qualitatively distinct inves tigative efforts. Both are drawing on Darwinian concepts, which may explain why many people have failed to discriminate them. One is the study of the evolution of the cognitive apparatus of living organisms, which is first and foremost the province of biologists and psychologists (H. C. Plotkin, Ed. , Learning, Development, and Culture: Essays in Evolu tionary Epistemology, New York, Wiley, 1984), although quite a few philosophers - professional or vocational - have also felt the need to express themselves on this vast subject (F. M. Wuketits, Ed. , Conce ts and Approaches in Evolutionary Epistemology, Dordrecht Boston, Reidel, 1984). The other approach deals with the evolution of science, and has been dominated hitherto by (allegedly) 'naturalized' philosophers; no book-length survey of this literature is available at present.
Available again, an influential book that offers a framework for understanding visual perception and considers fundamental questions about the brain and its functions. David Marr's posthumously published Vision (1982) influenced a generation of brain and cognitive scientists, inspiring many to enter the field. In Vision, Marr describes a general framework for understanding visual perception and touches on broader questions about how the brain and its functions can be studied and understood. Researchers from a range of brain and cognitive sciences have long valued Marr's creativity, intellectual power, and ability to integrate insights and data from neuroscience, psychology, and computation. This MIT Press edition makes Marr's influential work available to a new generation of students and scientists. In Marr's framework, the process of vision constructs a set of representations, starting from a description of the input image and culminating with a description of three-dimensional objects in the surrounding environment. A central theme, and one that has had far-reaching influence in both neuroscience and cognitive science, is the notion of different levels of analysis—in Marr's framework, the computational level, the algorithmic level, and the hardware implementation level. Now, thirty years later, the main problems that occupied Marr remain fundamental open problems in the study of perception. Vision provides inspiration for the continuing efforts to integrate knowledge from cognition and computation to understand vision and the brain.
Bayesian probability theory has emerged not only as a powerful tool for building computational theories of vision, but also as a general paradigm for studying human visual perception. This 1996 book provides an introduction to and critical analysis of the Bayesian paradigm. Leading researchers in computer vision and experimental vision science describe general theoretical frameworks for modelling vision, detailed applications to specific problems and implications for experimental studies of human perception. The book provides a dialogue between different perspectives both within chapters, which draw on insights from experimental and computational work, and between chapters, through commentaries written by the contributors on each others' work. Students and researchers in cognitive and visual science will find much to interest them in this thought-provoking collection.
This book provides an introduction to human visual perception suitable for readers studying or working in the fields of computer graphics and visualization, cognitive science, and visual neuroscience. It focuses on how computer graphics images are generated, rather than solely on the organization of the visual system itself; therefore, the text pro
Dynamic Neural Field Theory for Motion Perception provides a new theoretical framework that permits a systematic analysis of the dynamic properties of motion perception. This framework uses dynamic neural fields as a key mathematical concept. The author demonstrates how neural fields can be applied for the analysis of perceptual phenomena and its underlying neural processes. Also, similar principles form a basis for the design of computer vision systems as well as the design of artificially behaving systems. The book discusses in detail the application of this theoretical approach to motion perception and will be of great interest to researchers in vision science, psychophysics, and biological visual systems.
The Cambridge Handbook of Applied Perception Research covers core areas of research in perception with an emphasis on its application to real-world environments. Topics include multisensory processing of information, time perception, sustained attention, and signal detection, as well as pedagogical issues surrounding the training of applied perception researchers. In addition to familiar topics, such as perceptual learning, the Handbook focuses on emerging areas of importance, such as human-robot coordination, haptic interfaces, and issues facing societies in the twenty-first century (such as terrorism and threat detection, medical errors, and the broader implications of automation). Organized into sections representing major areas of theoretical and practical importance for the application of perception psychology to human performance and the design and operation of human-technology interdependence, it also addresses the challenges to basic research, including the problem of quantifying information, defining cognitive resources, and theoretical advances in the nature of attention and perceptual processes.
Aimed at students taking a course on visual perception, this textbook considers what it means for a man, a monkey and a computer to perceive the world. After an introduction and a discussion of methods, the book deals with how the environment produces a physical effect, how the resulting "image" is processed by the brain or by computer algorithms in order to produce a perception of "something out there". It also discusses color, form, motion, distance, and also the sensing of three dimensionality, before dealing with visual perception and its role in awareness and consciousness. The book concludes with discussions of perceptual development, blindness, and visual disorders. Visual perception is by its very nature an interdisciplinary subject that requires a basic understanding of a range of topics from diverse fields, and this is a very readable guide to all students whether they come from a neuroscience, psychology, cognitive science, robotics, or philosophy background.
This is the proceedings of the International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August 2006. The book presents 165 revised full papers, carefully chosen and reviewed, organized in topical sections on fuzzy systems, fuzzy-neuro-evolutionary hybrids, supervised, unsupervised and reinforcement learning, intelligent agent and Web applications, intelligent fault diagnosis, natural language processing and expert systems, natural language human-machine interface using artificial neural networks, and intelligent financial engineering.