DocumentCode
507923
Title
Detection of Straight Lines Using a Spiking Neural Network Model
Author
Wu, QingXiang ; McGinnity, T.M. ; Maguire, Liam ; Valderrama-Gonzalez, G.D. ; Cai, Jianyong
Author_Institution
Intell. Syst. Res. Centre, Univ. of Ulster at Magee, Londonderry, UK
Volume
2
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
385
Lastpage
389
Abstract
Receptive fields of neurons play various roles in biological neural networks. Based on a receptive field with the function of Hough transform, a spiking neural network model is proposed to detect straight lines in a visual image. Through the network, straight lines transform to corresponding neurons with high firing rates in the output neuron array. Simulation results show that straight lines can be detected by the network and firing rates of the corresponding neurons are referred to lengths of the lines. This model can be used to explain how a spiking neuron-based network can detect straight lines, and furthermore the model can be used in an artificial intelligent system.
Keywords
Hough transforms; neural nets; object detection; Hough transform; artificial intelligent system; biological neural networks; spiking neural network model; spiking neuron-based network; straight line detection; visual image; Artificial intelligence; Artificial neural networks; Biological neural networks; Biological system modeling; Circuits; Intelligent networks; Intelligent systems; Neural networks; Neurons; Visual system; Hough transform; receptive field; spiking neural networks; straight line detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3736-8
Type
conf
DOI
10.1109/ICNC.2009.484
Filename
5363996
Link To Document