Bio-inspired ganglion cell models for detecting horizontal and vertical movements

Machado, P. ORCID: 0000-0003-1760-3871, Oikonomou, A. ORCID: 0000-0002-5069-3971, Cosma, G. ORCID: 0000-0002-4663-6907 and McGinnity, T.M. ORCID: 0000-0002-9897-4748, 2018. Bio-inspired ganglion cell models for detecting horizontal and vertical movements. In: 2018 International Joint Conference on Neural Networks (IJCNN 2018), Rio de Janeiro, Brazil, 8-13 July 2018. (Forthcoming)

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Abstract

The retina performs the earlier stages of image processing in living beings and is composed of six different groups of cells, namely, the rods, cones, horizontal, bipolar, amacrine and ganglion cells. Each of those group of cells can be sub-divided into other types of cells that vary in shape, size, connectivity and functionality. Each cell is responsible for performing specific tasks in these early stages of biological image processing. Some of those cells are sensitive to horizontal and vertical movements. This paper proposes a multi-hierarchical spiking neural network architecture for detecting horizontal and vertical movements using a custom dataset which was generated in laboratory settings. The proposed architecture was designed to reflect the connectivity, behaviour and the number of layers found in the majority of vertebrates retinas, including humans. The architecture was trained using 2303 images and tested using 816 images. Simulation results revealed that each cell model is sensitive to vertical and horizontal movements with a detection error of 6.75 percent.

Item Type: Conference contribution
Creators: Machado, P., Oikonomou, A., Cosma, G. and McGinnity, T.M.
Date: July 2018
Divisions: Schools > School of Science and Technology
Depositing User: Jonathan Gallacher
Date Added: 01 May 2018 15:14
Last Modified: 15 Jul 2018 03:00
URI: http://irep.ntu.ac.uk/id/eprint/33415

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