Suchergebnisse - neighbourhood weighted fuzzy c‐means clustering algorithm

  1. 1

    Neighbourhood weighted fuzzy c-means clustering algorithm for image segmentation von Zaixin, Zhao, Lizhi, Cheng, Guangquan, Cheng

    ISSN: 1751-9659, 1751-9667
    Veröffentlicht: Stevenage The Institution of Engineering and Technology 01.03.2014
    Veröffentlicht in IET image processing (01.03.2014)
    “… Fuzzy c-means (FCM) clustering algorithm has been widely used in image segmentation …”
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  2. 2

    Generalised kernel weighted fuzzy C-means clustering algorithm with local information von Memon, Kashif Hussain, Lee, Dong-Ho

    ISSN: 0165-0114, 1872-6801
    Veröffentlicht: Elsevier B.V 01.06.2018
    Veröffentlicht in Fuzzy sets and systems (01.06.2018)
    “… Among them, the kernel weighted fuzzy local information C-means (KWFLICM) algorithm gives robust to noise image segmentation results by using local spatial image …”
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  3. 3

    An Unsupervised Snow Segmentation Approach Based on Dual-polarized Scattering Mechanism and Deep Neural Network von Liu, Chang, Li, Zhen, Wu, Zhipeng, Huang, Lei, Zhang, Ping, Li, Gang

    ISSN: 0196-2892, 1558-0644
    Veröffentlicht: New York IEEE 01.01.2023
    Veröffentlicht in IEEE transactions on geoscience and remote sensing (01.01.2023)
    “… availability has more advantages. In this study, an unsupervised algorithm for dry and wet snow discrimination, NSAE-WFCM, is proposed based on a variety of polarimetric features derived from H-α …”
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  4. 4

    Viewpoint‐Based Collaborative Feature‐Weighted Multi‐View Intuitionistic Fuzzy Clustering Using Neighborhood Information von Golzari Oskouei, Amin, Samadi, Negin, Tanha, Jafar, Bouyer, Asgarali, Arasteh, Bahman

    ISSN: 0925-2312
    Veröffentlicht: Elsevier B.V 07.02.2025
    Veröffentlicht in Neurocomputing (Amsterdam) (07.02.2025)
    “… This paper presents an intuitionistic fuzzy c-means-based clustering algorithm for multi-view clustering, addressing key challenges such as noise sensitivity, outlier influence, and the distinct …”
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  5. 5

    LIFWCM: local information-based fuzzy weighted C-means algorithm for image segmentation von Cui, Hanshuai, Zeng, Wenyi, Ma, Rong, Cheng, Dong, Chong, Qianpeng, Xu, Zeshui

    ISSN: 1573-7462, 0269-2821, 1573-7462
    Veröffentlicht: Dordrecht Springer Netherlands 11.11.2025
    Veröffentlicht in The Artificial intelligence review (11.11.2025)
    “… We propose LIFWCM, a local information-based fuzzy weighted C-means algorithm that assigns a single-pass, data-driven weight to each pixel by aggregating neighborhood intensity variation …”
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  6. 6

    Local search genetic algorithm-based possibilistic weighted fuzzy c-means for clustering mixed numerical and categorical data von Nguyen, Thi Phuong Quyen, Kuo, R. J., Le, Minh Duc, Nguyen, Thi Cuc, Le, Thi Huynh Anh

    ISSN: 0941-0643, 1433-3058
    Veröffentlicht: London Springer London 01.10.2022
    Veröffentlicht in Neural computing & applications (01.10.2022)
    “… Thus, this study proposes a local search genetic algorithm-based possibilistic weighted fuzzy c -means (LSGA-PWFCM …”
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  7. 7

    Fuzzy C-means clustering-based multi-label feature selection via weighted neighborhood mutual information von Sun, Lin, Guo, Jiaqi, Wu, Xuejiao, Xu, Jiucheng

    ISSN: 0020-0255
    Veröffentlicht: Elsevier Inc 01.11.2025
    Veröffentlicht in Information sciences (01.11.2025)
    “… •An association matrix is constructed through fuzzy synthesis to develop label enhancement.•Weighted neighborhood mutual information can handle the unbalanced label and redundancy …”
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  8. 8

    Generalised fuzzy c-means clustering algorithm with local information von Memon, Kashif Hussain, Lee, Dong-Ho

    ISSN: 1751-9659, 1751-9667
    Veröffentlicht: The Institution of Engineering and Technology 01.01.2017
    Veröffentlicht in IET image processing (01.01.2017)
    “… Much research has been conducted on fuzzy c-means (FCM) clustering algorithms for image segmentation that incorporate the local neighbourhood information …”
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  9. 9

    Modified Possibilistic Fuzzy C-means Clustering Driven by Weighted Residuals for Image Segmentation von Hu, Jianhua, Tong, Di, Song, Yan, Yu, Zhensheng

    ISSN: 1742-6588, 1742-6596
    Veröffentlicht: Bristol IOP Publishing 01.05.2025
    Veröffentlicht in Journal of physics. Conference series (01.05.2025)
    “… —specifically its sensitivity to noises and the occasional formation of coincident clusters, a modified probability fuzzy C-means algorithm driven by weighted residuals (WRMPFCM) has been proposed …”
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  10. 10

    A novel self-learning weighted fuzzy local information clustering algorithm integrating local and non-local spatial information for noise image segmentation von Song, Qiuyu, Wu, Chengmao, Tian, Xiaoping, Song, Yue, Guo, Xiaokang

    ISSN: 0924-669X, 1573-7497
    Veröffentlicht: New York Springer US 01.04.2022
    Veröffentlicht in Applied intelligence (Dordrecht, Netherlands) (01.04.2022)
    “… Fuzzy Local Information C-means Clustering (FLICM) is a widely used robust segmentation algorithm, which combines spatial information with the membership degree of adjacent pixels …”
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  11. 11

    A fuzzy clustering segmentation method based on neighborhood grayscale information for defining cucumber leaf spot disease images von Bai, Xuebing, Li, Xinxing, Fu, Zetian, Lv, Xiongjie, Zhang, Lingxian

    ISSN: 0168-1699, 1872-7107
    Veröffentlicht: Amsterdam Elsevier B.V 15.04.2017
    Veröffentlicht in Computers and electronics in agriculture (15.04.2017)
    “… An improved fuzzy C-means (FCM) algorithm is proposed in this paper. First, three runs of the marked-watershed algorithm, based on HSI space, are applied to isolate the target leaf …”
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  12. 12

    Enhanced Spatially Constrained Remotely Sensed Imagery Classification Using a Fuzzy Local Double Neighborhood Information C-Means Clustering Algorithm von Zhang, Hua, Bruzzone, Lorenzo, Shi, Wenzhong, Hao, Ming, Wang, Yunjia

    ISSN: 1939-1404, 2151-1535
    Veröffentlicht: Piscataway IEEE 01.08.2018
    “… This paper presents a fuzzy local double neighborhood information c-means (FLDNICM) clustering algorithm for remotely sensed imagery classification, which incorporates flexible and accurate local spatial and spectral information …”
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  13. 13

    Kernel-Based Robust Bias-Correction Fuzzy Weighted C-Ordered-Means Clustering Algorithm von Zhang, Wenyuan, Guo, Xijuan, Huang, Tianyu, Liu, Jiale, Chen, Jun

    ISSN: 2073-8994, 2073-8994
    Veröffentlicht: Basel MDPI AG 01.06.2019
    Veröffentlicht in Symmetry (Basel) (01.06.2019)
    “… The spatial constrained Fuzzy C-means clustering (FCM) is an effective algorithm for image segmentation …”
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  14. 14

    Local fuzzy geographically weighted clustering: a new method for geodemographic segmentation von Grekousis, George

    ISSN: 1365-8816, 1362-3087, 1365-8824
    Veröffentlicht: Abingdon Taylor & Francis 02.01.2021
    “… Fuzzy geographically weighted clustering has been proposed as an approach for improving fuzzy c-means algorithm when applied to geodemographic analysis …”
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  15. 15

    Intuitionistic fuzzy information-driven total Bregman divergence fuzzy clustering with multiple local information constraints for image segmentation von Wu, Chengmao, Huang, Congcong, Zhang, Jiajia

    ISSN: 0178-2789, 1432-2315
    Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2023
    Veröffentlicht in The Visual computer (01.01.2023)
    “… Aiming at the shortcoming of existing robust intuitionistic fuzzy clustering and its variant algorithms in the presence of high noise, we will explore a novel intuitionistic fuzzy clustering-related …”
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  16. 16

    Deep neighborhood structure driven interval type-2 kernel fuzzy c-means clustering with local versus non-local information von Wu, Chengmao, Peng, Siyun

    ISSN: 1380-7501, 1573-7721
    Veröffentlicht: New York Springer US 01.11.2023
    Veröffentlicht in Multimedia tools and applications (01.11.2023)
    “… Hence, this paper proposes a novel single fuzzifier interval type-2 kernel-based fuzzy local and non-local information c-means clustering driven by a deep neighborhood structure for strong noise image segmentation …”
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  17. 17

    VCoFWMVIFCM: An open-source code for viewpoint-based collaborative feature-weighted multi-view intuitionistic fuzzy clustering von Golzari Oskouei, Amin, Samadi, Negin, Bouyer, Asgarali, Tanha, Jafar

    ISSN: 2665-9638, 2665-9638
    Veröffentlicht: Elsevier B.V 01.03.2025
    Veröffentlicht in Software impacts (01.03.2025)
    “… We present VCoFWMVIFCM, an open-source Python implementation of a multi-view fuzzy clustering algorithm based on Intuitionistic Fuzzy c-Means (IFCM …”
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  18. 18

    An adaptive spatially constrained fuzzy c-means algorithm for multispectral remotely sensed imagery clustering von Zhang, Hua, Shi, Wenzhong, Hao, Ming, Li, Zhenxuan, Wang, Yunjia

    ISSN: 0143-1161, 1366-5901, 1366-5901
    Veröffentlicht: London Taylor & Francis 18.04.2018
    Veröffentlicht in International journal of remote sensing (18.04.2018)
    “… This paper presents a novel adaptive spatially constrained fuzzy c-means (ASCFCM) algorithm for multispectral remotely sensed imagery clustering by incorporating accurate local spatial and grey-level information …”
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  19. 19

    Kernel Possibilistic Fuzzy c-Means Clustering with Local Information for Image Segmentation von Memon, Kashif Hussain, Memon, Sufyan, Qureshi, Muhammad Ali, Alvi, Muhammad Bux, Kumar, Dileep, Shah, Rehan Ali

    ISSN: 1562-2479, 2199-3211
    Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2019
    Veröffentlicht in International journal of fuzzy systems (01.02.2019)
    “… The kernel weighted fuzzy c -means clustering with local information (KWFLICM) algorithm performs robustly to noise in research related to image segmentation using fuzzy c -means (FCM …”
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    A robust clustering algorithm using spatial fuzzy C-means for brain MR images von Alruwaili, Madallah, Siddiqi, Muhammad Hameed, Javed, Muhammad Arshad

    ISSN: 1110-8665
    Veröffentlicht: Elsevier B.V 01.03.2020
    Veröffentlicht in Egyptian informatics journal (01.03.2020)
    “… In medical images, a well-known clustering approach like Fuzzy C-Means widely used for segmentation …”
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