Suchergebnisse - neighbourhood weighted fuzzy c-means clustering algorithm

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

“… Fuzzy c-means (FCM) clustering algorithm has been widely used in image segmentation …”
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Generalised kernel weighted fuzzy C-means clustering algorithm with local information von Memon, Kashif Hussain, Lee, Dong-Ho

“… 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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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

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

“… •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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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

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

“… 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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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

“… Thus, this study proposes a local search genetic algorithm-based possibilistic weighted fuzzy c -means (LSGA-PWFCM …”
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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

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

“… —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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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

“… 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 von Wu, Chengmao, Peng, Siyun

“… 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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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

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

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

“… 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 von Memon, Kashif Hussain, Memon, Sufyan, Qureshi, Muhammad Ali, Alvi, Muhammad Bux, Kumar, Dileep, Shah, Rehan Ali

“… 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 von Wu, Chengmao, Zhou, Siyu

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

“… 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 von Golzari Oskouei, Amin, Samadi, Negin, Bouyer, Asgarali, Tanha, Jafar

“… 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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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

“… 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 von Song, Qiuyu, Wu, Chengmao, Tian, Xiaoping, Song, Yue, Guo, Xiaokang

“… 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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