RT Journal Article
T1 Recognition of partially occluded and rotated images with a network of spiking neurons
A1 Shin, Joo-Heon
A1 Smith, David
A1 Swiercz, Waldemar
A1 Staley, Kevin
A1 Rickard, J. Terry
A1 Montero De Juan, Francisco Javier
A1 Kurgan, Lukasz A.
A1 Cios, Krzysztof J.
AB In this paper, we introduce a novel system for recognition of partially occluded and rotated images. The system is based on a hierarchical network of integrate-and-fire spiking neurons with random synaptic connections and a novel organization process. The network generates integrated output sequences that are used for image classification. The proposed network is shown to provide satisfactory predictive performance given that the number of the recognition neurons and synaptic connections are adjusted to the size of the input image. Comparison of synaptic plasticity activity rule (SAPR) and spike timing dependant plasticity rules, which are used to learn connections between the spiking neurons, indicates that the former gives better results and thus the SAPR rule is used. Test results show that the proposed network performs better than a recognition system based on support vector machines.
PB IEEE
SN 1163-6046
YR 2010
FD 2010
LK https://hdl.handle.net/20.500.14352/44475
UL https://hdl.handle.net/20.500.14352/44475
LA eng
NO Joo-Heon Shin, Smith, D., Swiercz, W., Staley, K., Rickard, J.T., Montero, J., Kurgan, L.A., Cios, K.J.: Recognition of Partially Occluded and Rotated Images With a Network of Spiking Neurons. IEEE Trans. Neural Netw. 21, 1697-1709 (2010). https://doi.org/10.1109/TNN.2010.2050600
DS Docta Complutense
RD 18 dic 2025