NEUROCOMPUTATIONAL MODELLING OF DISTRIBUTED LEARNING FROM VISUAL STIMULI

Authors

  • Ankush Rai School of Computing Science & Engineering, VIT University, Chennai, Tamil Nadu, India
  • Jagadeesh Kannan R School of Computing Science & Engineering, VIT University, Chennai, Tamil Nadu, India

DOI:

https://doi.org/10.22159/ajpcr.2017.v10s1.19645

Keywords:

Neurocomputational Modelling, Machine Vision, Artificial Intelligence

Abstract

Neurocomputational modeling of visual stimuli can lead not only to identify the neural substrates of attention but also to test cognitive theories of
attention with applications on several visual media, robotics, etc. However, there are many research works done in cognitive model for linguistics,
but the studies regarding cognitive modeling of learning mechanisms for visual stimuli are falling back. Based on principles of operation cognitive
functionalities in human vision processing, the study presents the development of a computational neurocomputational cognitive model for visual
perception with detailed algorithmic descriptions. Here, four essential questions of cognition and visual attention is considered for logically
compressing into one unified neurocomputational model: (i) Segregation of special classes of stimuli and attention modulation, (ii) relation between
gaze movements and visual perception, (iii) mechanism of selective stimulus processing and its encoding in neuronal cells, and (iv) mechanism of
visual perception through autonomous relation proofing.

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Published

01-04-2017

How to Cite

Rai, A., and J. K. R. “NEUROCOMPUTATIONAL MODELLING OF DISTRIBUTED LEARNING FROM VISUAL STIMULI”. Asian Journal of Pharmaceutical and Clinical Research, vol. 10, no. 13, Apr. 2017, pp. 225-9, doi:10.22159/ajpcr.2017.v10s1.19645.

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