Výsledky vyhľadávania - neighbourhood weighted fuzzy c-means clustering algorithm

  1. 1

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

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

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

    ISSN: 0165-0114, 1872-6801
    Vydavateľské údaje: Elsevier B.V 01.06.2018
    Vydané v 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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    Journal Article
  3. 3

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

    ISSN: 0196-2892, 1558-0644
    Vydavateľské údaje: New York IEEE 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

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

    ISSN: 0020-0255
    Vydavateľské údaje: Elsevier Inc 01.11.2025
    Vydané v 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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  5. 5

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

    ISSN: 1573-7462, 0269-2821, 1573-7462
    Vydavateľské údaje: Dordrecht Springer Netherlands 11.11.2025
    Vydané v 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

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

    ISSN: 1751-9659, 1751-9667
    Vydavateľské údaje: The Institution of Engineering and Technology 01.01.2017
    Vydané v 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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    Journal Article
  7. 7

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

    ISSN: 0941-0643, 1433-3058
    Vydavateľské údaje: London Springer London 01.10.2022
    Vydané v 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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  8. 8

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

    ISSN: 0925-2312
    Vydavateľské údaje: Elsevier B.V 07.02.2025
    Vydané v 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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  9. 9

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

    ISSN: 1742-6588, 1742-6596
    Vydavateľské údaje: Bristol IOP Publishing 01.05.2025
    Vydané v 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

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

    ISSN: 1939-1404, 2151-1535
    Vydavateľské údaje: 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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    Deep neighborhood structure driven interval type-2 kernel fuzzy c-means clustering with local versus non-local information Autor Wu, Chengmao, Peng, Siyun

    ISSN: 1380-7501, 1573-7721
    Vydavateľské údaje: New York Springer US 01.11.2023
    Vydané v 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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  12. 12

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

    ISSN: 0143-1161, 1366-5901, 1366-5901
    Vydavateľské údaje: London Taylor & Francis 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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  13. 13

    Interval Type-2 enhanced possibilistic fuzzy C-means noisy image segmentation algorithm amalgamating weighted local information Autor Huang, Chengquan, Lei, Huan, Chen, Yang, Cai, Jianghai, Qin, Xiaosu, Peng, Jialei, Zhou, Lihua, Zheng, Lan

    ISSN: 0952-1976
    Vydavateľské údaje: Elsevier Ltd 01.11.2024
    “… Therefore, we propose a new noisy image segmentation algorithm based on weighted local information for interval type-2 enhanced possibilistic fuzzy C-means clustering…”
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  14. 14

    A robust clustering algorithm using spatial fuzzy C-means for brain MR images Autor Alruwaili, Madallah, Siddiqi, Muhammad Hameed, Javed, Muhammad Arshad

    ISSN: 1110-8665
    Vydavateľské údaje: Elsevier B.V 01.03.2020
    Vydané v 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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    Kernel Possibilistic Fuzzy c-Means Clustering with Local Information for Image Segmentation Autor Memon, Kashif Hussain, Memon, Sufyan, Qureshi, Muhammad Ali, Alvi, Muhammad Bux, Kumar, Dileep, Shah, Rehan Ali

    ISSN: 1562-2479, 2199-3211
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 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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    Robust Harmonic Fuzzy Partition Local Information C-Means Clustering for Image Segmentation Autor Wu, Chengmao, Zhou, Siyu

    ISSN: 2073-8994, 2073-8994
    Vydavateľské údaje: Basel MDPI AG 01.10.2024
    Vydané v Symmetry (Basel) (01.10.2024)
    “…) is proposed and the local convergence of the algorithm is rigorously proved using Zangwill’s theorem. Finally, inspired by the improved fuzzy local information C-means clustering…”
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  17. 17

    Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C -Means Clustering Autor Li, Guanglin, Wu, Jianhuang, Jia, Fucang, Wang, Changmiao, Elazab, Ahmed, Hu, Qingmao

    ISSN: 1748-670X, 1748-6718, 1748-6718
    Vydavateľské údaje: Cairo, Egypt Hindawi Publishing Corporation 01.01.2015
    “…An adaptively regularized kernel-based fuzzy C -means clustering framework is proposed for segmentation of brain magnetic resonance images…”
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    VCoFWMVIFCM: An open-source code for viewpoint-based collaborative feature-weighted multi-view intuitionistic fuzzy clustering Autor Golzari Oskouei, Amin, Samadi, Negin, Bouyer, Asgarali, Tanha, Jafar

    ISSN: 2665-9638, 2665-9638
    Vydavateľské údaje: Elsevier B.V 01.03.2025
    Vydané v 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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    Journal Article
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    A fuzzy clustering segmentation method based on neighborhood grayscale information for defining cucumber leaf spot disease images Autor Bai, Xuebing, Li, Xinxing, Fu, Zetian, Lv, Xiongjie, Zhang, Lingxian

    ISSN: 0168-1699, 1872-7107
    Vydavateľské údaje: Amsterdam Elsevier B.V 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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    A novel self-learning weighted fuzzy local information clustering algorithm integrating local and non-local spatial information for noise image segmentation Autor Song, Qiuyu, Wu, Chengmao, Tian, Xiaoping, Song, Yue, Guo, Xiaokang

    ISSN: 0924-669X, 1573-7497
    Vydavateľské údaje: New York Springer US 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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    Journal Article