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    CMVC

    The First International Workshop on Computational Models of the Visual Cortex: Hierarchies, Layers, Sparsity, Saliency and Attention

    Much has been advanced since the early works of the Nobel prize winners Hubel and Wiesel about the function of neurons in the primary visual cortex of cats’ brains. That work has been the source of inspiration of abundant neurophysiological studies to unveil the functionality of neurons in differe…

    Much has been advanced since the early works of the Nobel prize winners Hubel and Wiesel about the function of neurons in the primary visual cortex of cats’ brains. That work has been the source of inspiration of abundant neurophysiological studies to unveil the functionality of neurons in different areas of visual cortex. These experiments resulted in large amounts of data, which could then be used to design computational models to behave similarly to certain neurons in visual cortex. The contribution of such models is two-fold. They contribute to the better understanding of how visual information is processed in the brain, and they also contribute for the development of more robust algorithms in computer vision applications. The aim of this workshop is to bring together recent development of computational modelling of the visual cortex of the brain: Single cell modeling. Feedforward, feedback and inhibitory mechanisms. The appearance of neuronal properties: sparsity and selectivity. Circuitry: hierarchical representations and connections between layers. Selecting where to look: saliency and attention.

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    Editor(s): Junichi Suzuki (Associate Professor, Dept of Comp. Science, University of Massachusetts, Boston, 10 Morrissey Blvd., Boston, MA 02125, USA), Tadashi Nakano (Associate Professor, Osaka University, 1-3 Yamadaoka, Suita, Osaka 565-0871, Japan) and Henry Hess (Associate Professor, Department of Biomedical Engineering, Columbia University, 351L Engineering Terrace, MC 8904, 1210 Amsterdam Avenue, New York, NY 10027)
    Publisher
    ACM
    ISBN
    978-1-63190-100-3
    ISSN
    -
    Conference dates
    3rd–5th Dec 2015
    Location
    New York City, United States
    Appeared in EUDL
    2016-05-24

    Copyright © 2016–2025 ICST

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    Showing 1–10 of 10 results
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    • 1
    • A Deconvolutional Competitive Algorithm for Building Sparse Hierarchical Representations

      Research Article in The First International Workshop on Computational Models of the Visual Cortex: Hierarchies, Layers, Sparsity, Saliency and Attention

      Dylan Paiton, Sheng Lundquist, William Shainin, Xinhua Zhang, Peter Schultz, Garrett Kenyon
    • A Deconvolutional Strategy for Implementing Large Patch Sizes Supports Improved Image Classification

      Research Article in The First International Workshop on Computational Models of the Visual Cortex: Hierarchies, Layers, Sparsity, Saliency and Attention

      Xinhua Zhang, Garrett Kenyon
    • A Study of the Role of the Maintained-Discharge Parameter in the Divisive Normalization Model of V1 Neurons

      Research Article in The First International Workshop on Computational Models of the Visual Cortex: Hierarchies, Layers, Sparsity, Saliency and Attention

      Tadamasa Sawada, Alexander Petrov
    • Changes in variance of neuronal signals may be perceptually relevant for stereo vision

      Research Article in The First International Workshop on Computational Models of the Visual Cortex: Hierarchies, Layers, Sparsity, Saliency and Attention

      Nela Cicmil, Andrew Parker, Kristine Krug
    • Comparing the brainʼs representation of shape to that of a deep convolutional neural network

      Research Article in The First International Workshop on Computational Models of the Visual Cortex: Hierarchies, Layers, Sparsity, Saliency and Attention

      Dean Pospisil, Anitha Pasupathy, Wyeth Bair
    • Event-based optical flow on neuromorphic hardware

      Research Article in The First International Workshop on Computational Models of the Visual Cortex: Hierarchies, Layers, Sparsity, Saliency and Attention

      Tobias Brosch, Heiko Neumann
    • Learning Abstract Classes using Deep Learning

      Research Article in The First International Workshop on Computational Models of the Visual Cortex: Hierarchies, Layers, Sparsity, Saliency and Attention

      Sebastian Stabinger, Antonio Rodríguez-Sánchez, Justus Piater
    • Propagating Waves as a Cortical Mechanism of Direction-Selectivity in V1 Motion Cells

      Research Article in The First International Workshop on Computational Models of the Visual Cortex: Hierarchies, Layers, Sparsity, Saliency and Attention

      Stewart Heitmann, Bard Ermentrout
    • Spatial scale of correlated signals in 7T BOLD imaging

      Research Article in The First International Workshop on Computational Models of the Visual Cortex: Hierarchies, Layers, Sparsity, Saliency and Attention

      Andrew Parker, Holly Bridge, Gaelle Coullon
    • Towards a mesoscopic-level canonical circuit definition for visual cortical processing

      Research Article in The First International Workshop on Computational Models of the Visual Cortex: Hierarchies, Layers, Sparsity, Saliency and Attention

      Georg Layher, Tobias Brosch, Heiko Neumann
    • 1
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