Please use this identifier to cite or link to this item:
https://doi.org/10.1016/j.imavis.2005.07.008
DC Field | Value | |
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dc.title | Colour image segmentation using the self-organizing map and adaptive resonance theory | |
dc.contributor.author | Yeo, N.C. | |
dc.contributor.author | Lee, K.H. | |
dc.contributor.author | Venkatesh, Y.V. | |
dc.contributor.author | Ong, S.H. | |
dc.date.accessioned | 2014-06-17T02:41:49Z | |
dc.date.available | 2014-06-17T02:41:49Z | |
dc.date.issued | 2005-11-01 | |
dc.identifier.citation | Yeo, N.C., Lee, K.H., Venkatesh, Y.V., Ong, S.H. (2005-11-01). Colour image segmentation using the self-organizing map and adaptive resonance theory. Image and Vision Computing 23 (12) : 1060-1079. ScholarBank@NUS Repository. https://doi.org/10.1016/j.imavis.2005.07.008 | |
dc.identifier.issn | 02628856 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/55325 | |
dc.description.abstract | We propose a new competitive-learning neural network model for colour image segmentation. The model, which is based on the adaptive resonance theory (ART) of Carpenter and Grossberg and on the self-organizing map (SOM) of Kohonen, overcomes the limitations of (i) the stability-plasticity trade-offs in neural architectures that employ ART; and (ii) the lack of on-line learning property in the SOM. In order to explore the generation of a growing feature map using ART and to motivate the main contribution, we first present a preliminary experimental model, SOMART, based on Fuzzy ART. Then we propose the new model, SmART, that utilizes a novel lateral control of plasticity to resolve the stability-plasticity problem. SmART has been experimentally found to perform well in RGB colour space, and is believed to be more coherent than Fuzzy ART. © 2005 Elsevier Ltd. All rights reserved. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.imavis.2005.07.008 | |
dc.source | Scopus | |
dc.subject | Adaptive resonance theory | |
dc.subject | Colour image segmentation | |
dc.subject | Lateral control | |
dc.subject | Network plasticity | |
dc.subject | Network stability | |
dc.subject | Neural networks | |
dc.subject | Self-organizing map | |
dc.type | Article | |
dc.contributor.department | MECHANICAL ENGINEERING | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.description.doi | 10.1016/j.imavis.2005.07.008 | |
dc.description.sourcetitle | Image and Vision Computing | |
dc.description.volume | 23 | |
dc.description.issue | 12 | |
dc.description.page | 1060-1079 | |
dc.description.coden | IVCOD | |
dc.identifier.isiut | 000232423400004 | |
Appears in Collections: | Staff Publications |
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