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John K. Tsotsos [18]J. Tsotsos [2]J. K. Tsotsos [2]John Tsotsos [1]
  1. Analyzing vision at the complexity level.John K. Tsotsos - 1990 - Behavioral and Brain Sciences 13 (3):423-445.
    The general problem of visual search can be shown to be computationally intractable in a formal, complexity-theoretic sense, yet visual search is extensively involved in everyday perception, and biological systems manage to perform it remarkably well. Complexity level analysis may resolve this contradiction. Visual search can be reshaped into tractability through approximations and by optimizing the resources devoted to visual processing. Architectural constraints can be derived using the minimum cost principle to rule out a large class of potential solutions. The (...)
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  2.  25
    A complexity level analysis of vision.John K. Tsotsos - 1990 - Behavioral and Brain Sciences 13 (3):423-445.
    The general problem of visual search can be shown to be computationally intractable in a formal, complexity-theoretic sense, yet visual search is extensively involved in everyday perception, and biological systems manage to perform it remarkably well. Complexity level analysis may resolve this contradiction. Visual search can be reshaped into tractability through approximations and by optimizing the resources devoted to visual processing. Architectural constraints can be derived using the minimum cost principle to rule out a large class of potential solutions. The (...)
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  3.  13
    Modeling visual attention via selective tuning.John K. Tsotsos, Scan M. Culhane, Winky Yan Kei Wai, Yuzhong Lai, Neal Davis & Fernando Nuflo - 1995 - Artificial Intelligence 78 (1-2):507-545.
  4.  40
    Neurobiology of Attention.Laurent Itti, Geraint Rees & John K. Tsotsos (eds.) - 2005 - Academic Press.
    This book presents a state-of-the-art multidisciplinary perspective on psychological, physiological and computational approaches to understanding the ...
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  5.  20
    Schemas: Not yet an interlingua for the brain sciences.John K. Tsotsos - 1987 - Behavioral and Brain Sciences 10 (3):447-448.
  6.  73
    A brief and selective history of attention.John K. Tsotsos, Laurent Itti & Geraint Rees - 2005 - In Laurent Itti, Geraint Rees & John K. Tsotsos (eds.), Neurobiology of Attention. Academic Press.
  7. Models of bottom-up attention and saliency.Laurent Itti, G. Rees & J. K. Tsotsos - 2005 - In Laurent Itti, Geraint Rees & John K. Tsotsos (eds.), Neurobiology of Attention. Academic Press. pp. 582.
  8.  5
    Behaviorist intelligence and the scaling problem.John K. Tsotsos - 1995 - Artificial Intelligence 75 (2):135-160.
  9.  22
    Cognitive programs: software for attention's executive.John K. Tsotsos & Wouter Kruijne - 2014 - Frontiers in Psychology 5.
  10.  31
    A little complexity analysis goes a long way.John K. Tsotsos - 1990 - Behavioral and Brain Sciences 13 (3):458-469.
  11.  28
    Computational resources do constrain behavior.John K. Tsotsos - 1991 - Behavioral and Brain Sciences 14 (3):506-507.
  12.  9
    Is complexity theory appropriate for analyzing biological systems?John K. Tsotsos - 1991 - Behavioral and Brain Sciences 14 (4):770-773.
  13.  21
    Complexity Level Analysis Revisited: What Can 30 Years of Hindsight Tell Us about How the Brain Might Represent Visual Information?John K. Tsotsos - 2017 - Frontiers in Psychology 8.
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  14.  7
    Empirically-derived estimates of the complexity of labeling line drawings of polyhedral scenes.P. Parodi, R. Lancewicki, A. Vijh & J. K. Tsotsos - 1998 - Artificial Intelligence 105 (1-2):47-75.
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  15.  11
    A Tour of This Volume.Michael Tombu, Neil Bruce, Albert Rothenstein & John K. Tsotsos - 2005 - In Laurent Itti, Geraint Rees & John K. Tsotsos (eds.), Neurobiology of Attention. Academic Press.
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  16.  12
    Attentive selection penetrates (almost) the entire visual system.John K. Tsotsos - 1999 - Behavioral and Brain Sciences 22 (3):397-397.
    Pylyshyn claims that if a system is cognitively penetrable, its function depends in a semantically coherent way to the organism's goals and beliefs. He rejects evidence of attentional modulation observed in neurons within the visual system, claiming that any modulation seen is not logically related to goals and behavior. I present some of this evidence and claim that it is connected in exactly the way Pylyshyn requires and thus it refutes his main thesis.
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  17.  15
    Connectionist computing and neural machinery: Examining the test of “timing”.John K. Tsotsos - 1986 - Behavioral and Brain Sciences 9 (1):106-107.
  18.  21
    Computation, PET images, and attention.John K. Tsotsos - 1995 - Behavioral and Brain Sciences 18 (2):372-372.
    Posner & Raichle (1994) is a nice addition to the Scientific American Library and the average reader will both enjoy the book and learn a great deal. As an activeresearcher, however, I find the book disappointing in many respects. My two major disappointments are in the illusion of computation that is created throughout the volume and in the inadequate perspective of the presentation on visual attention.
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  19.  35
    Exactly which emperor is Penrose talking about?John K. Tsotsos - 1990 - Behavioral and Brain Sciences 13 (4):686-687.
  20.  31
    Limited Capacity of Any Realizable Perceptual System Is a Sufficient Reason for Attentive Behavior.John K. Tsotsos - 1997 - Consciousness and Cognition 6 (2-3):429-436.