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Detection of Straight Lines Using a Spiking Neural Network Model

Wu, Qingxiang, McGinnity, TM, Maguire, Liam, Valderrama, German and Cai, Jianyong (2009) Detection of Straight Lines Using a Spiking Neural Network Model. In: 2009 Fifth International Conference on Natural Computation, Tianjian, China. IEEE/IET Electronic Library (IEL), VDE VERLAG Conference Proceedings. Vol 2 5 pp. [Conference contribution]

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URL: http://doi.ieeecomputersociety.org/10.1109/ICNC.2009.484

DOI: 10.1109/ICNC.2009.484

Abstract

Receptive fields of neurons play various rolesin biological neural networks. Based on a receptive field withthe function of Hough transform, a spiking neural networkmodel is proposed to detect straight lines in a visual image.Through the network, straight lines transform tocorresponding neurons with high firing rates in the outputneuron array. Simulation results show that straight lines canbe detected by the network and firing rates of thecorresponding neurons are referred to lengths of the lines. Thismodel can be used to explain how a spiking neuron-basednetwork can detect straight lines, and furthermore the modelcan be used in an artificial intelligent system.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:20037
Deposited By: Mr German Valderrama
Deposited On:23 Sep 2011 13:18
Last Modified:23 Sep 2011 13:18

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