Application of modified FCM with additional data to area division of images

Kaoru Hirota; Kazuya Iwama

doi:10.1016/0020-0255(88)90041-2

Application of modified FCM with additional data to area division of images

Kaoru Hirota^*, Kazuya Iwama

^*此作品的通讯作者

Hosei University

科研成果: 期刊稿件 › 文章 › 同行评审

5 引用（Scopus）

摘要

A modified version of fuzzy c-means, called fuzzy c-means with additional data (FCM-AD), is presented in order to achieve robustness against a few outliers. Usefulness of the algorithm is confirmed through simulation experiments on both artificial data sets and real remote sensing imagery data. Results of various fuzzy clustering algorithms applied to imagery data are also investigated from a viewpoint of subjective entropy of probabilistic sets.

源语言	英语
页（从-至）	213-230
页数	18
期刊	Information Sciences
卷	45
期	2
DOI	https://doi.org/10.1016/0020-0255(88)90041-2
出版状态	已出版 - 7月 1988
已对外发布	是

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10.1016/0020-0255(88)90041-2

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Hirota, K., & Iwama, K. (1988). Application of modified FCM with additional data to area division of images. Information Sciences, 45(2), 213-230. https://doi.org/10.1016/0020-0255(88)90041-2

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abstract = "A modified version of fuzzy c-means, called fuzzy c-means with additional data (FCM-AD), is presented in order to achieve robustness against a few outliers. Usefulness of the algorithm is confirmed through simulation experiments on both artificial data sets and real remote sensing imagery data. Results of various fuzzy clustering algorithms applied to imagery data are also investigated from a viewpoint of subjective entropy of probabilistic sets.",

author = "Kaoru Hirota and Kazuya Iwama",

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AB - A modified version of fuzzy c-means, called fuzzy c-means with additional data (FCM-AD), is presented in order to achieve robustness against a few outliers. Usefulness of the algorithm is confirmed through simulation experiments on both artificial data sets and real remote sensing imagery data. Results of various fuzzy clustering algorithms applied to imagery data are also investigated from a viewpoint of subjective entropy of probabilistic sets.

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Application of modified FCM with additional data to area division of images

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