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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ukrit Marung | en_US |
dc.contributor.author | Nipon Theera-Umpon | en_US |
dc.contributor.author | Sansanee Auephanwiriyakul | en_US |
dc.date.accessioned | 2018-09-04T04:19:23Z | - |
dc.date.available | 2018-09-04T04:19:23Z | - |
dc.date.issued | 2011-12-01 | en_US |
dc.identifier.other | 2-s2.0-84857264400 | en_US |
dc.identifier.other | 10.1109/ISPACS.2011.6146206 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84857264400&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/49856 | - |
dc.description.abstract | Clustering method has been applied in many fields, including data mining, machine learning, information retrieval, and image analysis. In this paper, we propose a visual clustering method based on the genetic algorithm (GA) and image manipulation. The proposed method automatically determines the number of clusters in a binary image without using distance measures. There are three processes of the proposed method, i.e., creating the object table, mapping the object table into a binary image, and clustering objects in the binary image by using the GA and image manipulation. The effectiveness of the proposed method is tested on both synthetic data sets and a real data set. The experimental results show that the proposed method can effectively construct the clusters in both synthetic and real data sets. © 2011 IEEE. | en_US |
dc.subject | Computer Science | en_US |
dc.title | Visual clustering method using genetic algorithm and image manipulation | en_US |
dc.type | Conference Proceeding | en_US |
article.title.sourcetitle | 2011 International Symposium on Intelligent Signal Processing and Communications Systems: "The Decade of Intelligent and Green Signal Processing and Communications", ISPACS 2011 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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