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Psychology

D-Index
37
Citations
8619
World Ranking
9063
National Ranking
4805

Overview

John E. Hummel is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research predominantly lies within the field of Neuroscience, with a particular focus on Cognitive Neuroscience. The scientist's work encompasses several subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Geometry and Topology, and Experimental and Cognitive Psychology.

The main topics explored in their research include:

  • Visual perception and processing mechanisms
  • Neural and Behavioral Psychology Studies
  • Neural dynamics and brain function
  • Neural Networks and Applications
  • Visual Attention and Saliency Detection
  • Morphological variations and asymmetry
  • Face Recognition and Perception

John E. Hummel has contributed to various publication venues. Their frequent publication outlets are:

  • Journal of Vision
  • Journal of Experimental Psychology General
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Behavioral and Brain Sciences
  • Cognition

Among recent papers authored or coauthored by John E. Hummel are:

  • "Human shape representations are not an emergent property of learning to classify objects." (2023) - Journal of Experimental Psychology General
  • "Human shape representations are not an emergent property of learning to classify objects." (2021) - bioRxiv (Cold Spring Harbor Laboratory)
  • "Clarifying status of DNNs as models of human vision" (2023) - Behavioral and Brain Sciences
  • "How does multidimensional complexity impact processing efficiency in visual search?" (2021) - Journal of Vision
  • "Asynchronous visual flicker alters perceived curvature" (2021) - Journal of Vision

Their frequent coauthors include:

  • Alejandro Lleras
  • Simona Buetti
  • Rachel Flood Heaton
  • Gaurav Malhotra
  • Marin Dujmović

Best Publications

  • Distributed representations of structure: A theory of analogical access and mapping.

    John E. Hummel;Keith J. Holyoak

  • Dynamic binding in a neural network for shape recognition.

    John E. Hummel;Irving Biederman

  • A symbolic-connectionist theory of relational inference and generalization.

    John E. Hummel;Keith J. Holyoak

  • A Theory of the Discovery and Predication of Relational Concepts.

    Leonidas A. A. Doumas;John E. Hummel;Catherine M. Sandhofer

  • Countering antivaccination attitudes

    Zachary Horne;Derek Powell;John E. Hummel;Keith J. Holyoak

  • A Neurocomputational Model of Analogical Reasoning and its Breakdown in Frontotemporal Lobar Degeneration

    Robert G. Morrison;Daniel C. Krawczyk;Keith J. Holyoak;John E. Hummel

  • Relational integration, inhibition, and analogical reasoning in older adults.

    Indre V. Viskontas;Robert G. Morrison;Keith J. Holyoak;John E. Hummel

  • A neurocomputational system for relational reasoning

    Barbara J. Knowlton;Robert G. Morrison;John E. Hummel;Keith J. Holyoak

  • Where View-based Theories Break Down: The Role of Structure in Shape Perception and Object Recognition

    John E. Hummel

  • Complementary solutions to the binding problem in vision: Implications for shape perception and object recognition

    John E. Hummel

  • Metric invariance in object recognition: a review and further evidence.

    Eric E. Cooper;Irving Biederman;John E. Hummel

  • Relational Reasoning in a Neurally Plausible Cognitive Architecture An Overview of the LISA Project

    John E. Hummel;Keith J. Holyoak

  • Familiar interacting object pairs are perceptually grouped.

    Collin Green;John E. Hummel

  • Approaches to Modeling Human Mental Representations: What Works, What Doesn't, and Why.

    Leonidas A. A. Doumas;John E. Hummel

  • An architecture for rapid, hierarchical structural description

    John E Hummel;Brian J. Stankiewicz

  • The role of attention in priming for left-right reflections of object images: evidence for a dual representation of object shape.

    Brian J. Stankiewicz;Brian J. Stankiewicz;John E. Hummel;Eric E. Cooper

  • The use of diagrams in analogical problem solving.

    Roberto Pedone;John E. Hummel;Keith J. Holyoak

  • Causality and the allocation of attention during comprehension.

    Charles R. Fletcher;John E. Hummel;Chad J. Marsolek

  • Comparison-induced decoy effects.

    Jessica M. Choplin;John E. Hummel

  • Two Roles for Attention in Shape Perception: A Structural Description Model of Visual Scrutiny

    John E. Hummel;Brian J. Stankiewicz

  • The Proper Treatment of Symbols in a Connectionist Architecture

    Keith J. Holyoak;John E. Hummel

Frequent Co-Authors

Keith J. Holyoak
Keith J. Holyoak University of California, Los Angeles
Jules Davidoff
Jules Davidoff Goldsmiths University of London
Irving Biederman
Irving Biederman University of Southern California
Barbara J. Knowlton
Barbara J. Knowlton University of California, Los Angeles
Daniel C. Krawczyk
Daniel C. Krawczyk The University of Texas at Dallas
Philip J. Kellman
Philip J. Kellman University of California, Los Angeles
Brian H. Ross
Brian H. Ross University of Illinois at Urbana-Champaign
Daniel J. Simons
Daniel J. Simons University of Illinois at Urbana-Champaign
Michael J. Tarr
Michael J. Tarr Carnegie Mellon University

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