Literature DB >> 17925240

Attention in hierarchical models of object recognition.

Dirk B Walther1, Christof Koch.   

Abstract

Object recognition and visual attention are tightly linked processes in human perception. Over the last three decades, many models have been suggested to explain these two processes and their interactions, and in some cases these models appear to contradict each other. We suggest a unifying framework for object recognition and attention and review the existing modeling literature in this context. Furthermore, we demonstrate a proof-of-concept implementation for sharing complex features between recognition and attention as a mode of top-down attention to particular objects or object categories.

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Year:  2007        PMID: 17925240     DOI: 10.1016/S0079-6123(06)65005-X

Source DB:  PubMed          Journal:  Prog Brain Res        ISSN: 0079-6123            Impact factor:   2.453


  11 in total

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2.  Arousal-Biased Competition in Perception and Memory.

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3.  A computational model of fMRI activity in the intraparietal sulcus that supports visual working memory.

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6.  There's Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task.

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Review 7.  Visual cognition.

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8.  Neural Correlates of Auditory Figure-Ground Segregation Based on Temporal Coherence.

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Journal:  Cereb Cortex       Date:  2016-06-19       Impact factor: 5.357

9.  Top-down feedback in an HMAX-like cortical model of object perception based on hierarchical Bayesian networks and belief propagation.

Authors:  Salvador Dura-Bernal; Thomas Wennekers; Susan L Denham
Journal:  PLoS One       Date:  2012-11-05       Impact factor: 3.240

10.  Segregation of complex acoustic scenes based on temporal coherence.

Authors:  Sundeep Teki; Maria Chait; Sukhbinder Kumar; Shihab Shamma; Timothy D Griffiths
Journal:  Elife       Date:  2013-07-23       Impact factor: 8.140

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