EDCWRN: efficient deep clustering with the weight of representations and the help of neighbors
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-022-03895-5.pdf
Reference55 articles.
1. Oskouei AG, Hashemzadeh M, Asheghi B, Balafar M-A (2021) "CGFFCM: Cluster-weight and Group-local Feature-weight learning in Fuzzy C-Means clustering algorithm for color image segmentation," Appl Soft Comput, p. 108005, 2021/10/26/ 2021. https://doi.org/10.1016/j.asoc.2021.108005
2. Golzari Oskouei A, Balafar MA, Motamed C (2021) FKMAWCW: Categorical fuzzy k-modes clustering with automated attribute-weight and cluster-weight learning. Chaos, Solitons Fractals 153:111494. https://doi.org/10.1016/j.chaos.2021.111494
3. Hashemzadeh M, Golzari Oskouei A, Farajzadeh N (2019) New fuzzy C-means clustering method based on feature-weight and cluster-weight learning. Appl Soft Comput 78:324–345. https://doi.org/10.1016/j.asoc.2019.02.038
4. Ke G, Hong Z, Yu W, Zhang X, Liu Z (2022) "Efficient multi-view clustering networks," Appl Intell https://doi.org/10.1007/s10489-021-03129-0
5. Pourbahrami S, Balafar MA, Khanli LM, Kakarash ZA (2020) A survey of neighborhood construction algorithms for clustering and classifying data points. Comp Sci Rev 38:100315. https://doi.org/10.1016/j.cosrev.2020.100315
Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. SSFCM-FWCW: Semi-Supervised Fuzzy C-Means method based on Feature-Weight and Cluster-Weight learning;Software Impacts;2024-09
2. Deep image clustering: A survey;Neurocomputing;2024-09
3. Feature-weight and cluster-weight learning in fuzzy c-means method for semi-supervised clustering;Applied Soft Computing;2024-08
4. An overview on deep clustering;Neurocomputing;2024-07
5. Neighborhood information based semi-supervised fuzzy C-means employing feature-weight and cluster-weight learning;Chaos, Solitons & Fractals;2024-04
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3