Computational Intelligence and Neuroscience

Biologically Inspired Methods for Imaging, Cognition, Vision, and Intelligence


Publishing date
18 Dec 2015
Status
Published
Submission deadline
31 Jul 2015

Lead Editor

1Alcorn State University, Lorman, USA

2US Air Force Research Laboratory (AFRL), Rome, USA

3University of Louisville, Louisville, USA


Biologically Inspired Methods for Imaging, Cognition, Vision, and Intelligence

Description

State-of-the-art image analysis and pattern recognition techniques have been successfully applied to a wide variety of industrial fields such as medical imaging, remote sensing, machine learning, computer vision, biometrics, and visualization. However, the current methods of image analysis, computer vision, and artificial intelligence cannot achieve the performance of human visual and cognitive abilities although advances have progressed in hardware including optics, electronics, and computers. As Scott (1990, Science of Vision) stated, “the evolution of biological vision is gradual (incremental) and top down with basic modules and primitive architectural structures preserved.” The future of computer vision will be biologically inspired (Overington 1992) that has much in common with human vision as a unified science of vision (Scott 1990). Thus, computational photography, cognition, and intelligence have recently become the sources of interactive scientific researches.

This special issue focuses on biologically inspired or nature-driven approaches to computer vision. The success of computer vision and intelligence may start from the data representation of the real world (signal sensing and imaging), through analysis and cognition (learning, modelling, and classification), to achieve a certain level of performance (model revision, autolearning, and improvement). The following three areas: image perception inspired by human vision system; bioinspired image sensing and processing methods; and bioinspired image analysis, pattern recognition, computer vision, and artificial intelligence approaches, were tackled in this special issue.

Potential topics include, but are not limited to:

  • Area I (Image Perception): evolution of vision system and overview of visual process; retinal image perception and processes; visual signal transportation and relay; modeling of human vision
  • Area II (Bioinspired Image Sensing and Image Analysis): image sensing and sampling processes; bioinspired sensor network; bioinspired imaging and visualization techniques; simulation and modeling of visual analysis and cognition
  • Area III (Bioinspired Pattern Recognition and Intelligence): bioinspired feature extraction, image representation, and image analysis; Bioinspired Machine Learning and adaptive learning, pattern recognition and computer vision; survey of bioinspired cognition and artificial intelligence methods with suggestions of future research directions
Computational Intelligence and Neuroscience
 Journal metrics
Acceptance rate27%
Submission to final decision80 days
Acceptance to publication40 days
CiteScore2.270
Impact Factor2.154
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