Search Results - prior entropy fuzzy C-Means clustering algorithm

Automatic segmentation algorithm for high-spatial-resolution remote sensing images based on self-learning super-pixel convolutional network by Yang, Zenan, Niu, Haipeng, Huang, Liang, Wang, Xiaoxuan, Fan, Liangxin, Xiao, Dongyang

“…Super-pixel algorithms based on convolutional neural networks with fuzzy C-means clustering are widely used for high-spatial-resolution remote sensing images segmentation…”
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A new approach for clustering in desulfurization system based on modified framework for gypsum slurry quality monitoring by Gu, Hui, Cui, Yanfeng, Zhu, Hongxia, Xue, Rui, Si, Fengqi

“… In this paper, an on-line clustering framework has been proposed to monitor gypsum slurry quality in desulfurization system based on data mining. Compound parameterγ…”
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Automatic Fuzzy Clustering Framework for Image Segmentation by Lei, Tao, Liu, Peng, Jia, Xiaohong, Zhang, Xuande, Meng, Hongying, Nandi, Asoke K.

“…Clustering algorithms by minimizing an objective function share a clear drawback of having to set the number of clusters manually…”
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3-D Gravity Anomaly Inversion Based on Improved Guided Fuzzy C-Means Clustering Algorithm by Liu, Sheng, Jin, Shuanggen

“… of the Earth’s internal structure. Guided fuzzy C -means clustering inversion (FCM) is normally applied for the Tikhonov regularized inversion, but has the shortcoming of uniform model parameter shrinkage, leading to inaccuracy…”
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Overflow remote warning using improved fuzzy c-means clustering in IoT monitoring system based on multi-access edge computing by Liang, Haibo, Liu, Gang, Gao, Jianchong, Khan, Muhammad Junaid

“… of the cloud computing platform. At the same time, for the current domestic and international artificial intelligence-based overflow warning model, it needs a large amount of prior knowledge or training data before use…”
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Interval Type-2 Relative Entropy Fuzzy C-Means clustering by Zarinbal, M., Fazel Zarandi, M.H., Turksen, I.B.

“… In this paper, investigating the latter uncertainties is our concern and Interval Type-2 Relative Entropy Fuzzy C-Means (IT2 REFCM…”
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New semi-supervised fuzzy C-means clustering with asymmetric deviation constraints and fast algorithm by Wu, Chengmao, Hou, Jun

“… algorithm’s convergence is analyzed.•A fast semi-supervised fuzzy clustering algorithm is presented…”
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Segmentation of Images using Automatic Fuzzy Clustering Framework by Gannavaram V, Tulasi Krishna, Kandhikonda, Uma Maheshwar, Gade, Preetham, Sunkaraneni, Sumanth, Raghotham Reddy, Ganta

“…Clustering is grouping up of data points. Using clustering algorithms, the data points can be grouped with similar properties…”
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Multispectral Image Segmentation Based on a Fuzzy Clustering Algorithm Combined with Tsallis Entropy and a Gaussian Mixture Model by Xu, Yan, Chen, Ruizhi, Li, Yu, Zhang, Peng, Yang, Jie, Zhao, Xuemei, Liu, Mengyun, Wu, Dewen

“… The algorithm uses the fuzzy Tsallis entropy as regularization item for fuzzy C-means (FCM) and improves dissimilarity measure using the negative logarithm of the Gaussian Mixture Model (GMM…”
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Adaptive fuzzy weighted C-mean image segmentation algorithm combining a new distance metric and prior entropy by Song, Sensen, Jia, Zhenhong, Shi, Fei, Wang, Junnan, Ni, Dongdong

“… To overcome these shortcomings, we propose an adaptive fuzzy weighted C-mean image segmentation algorithm that combines a new distance metric and prior entropy…”
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Hybrid Preprocessing Algorithm for Endmember Extraction Using Clustering, Over-Segmentation, and Local Entropy Criterion by Kowkabi, Fatemeh, Ghassemian, Hassan, Keshavarz, Ahmad

“…) extraction algorithms. Hence, we take advantage of a top-down over-segmentation algorithm in combination with fuzzy c-means (FCM…”
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Semi-supervised fuzzy clustering with metric learning and entropy regularization by Yin, Xuesong, Shu, Ting, Huang, Qi

“… To address these problems, we develop a novel semi-supervised metric-based fuzzy clustering algorithm called SMUC by introducing metric learning and entropy regularization simultaneously…”
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Clustering Validity Evaluation Functions of Fuzzy C-means Clustering Algorithm by Wang, Guan, Xing, Cheng, Wang, Jie-Sheng, Wang, Hong-Yu, Liu, Jia-Xu

“…Fuzzy C-means (FCM) clustering algorithm is a method mainly applied to machine learning and data mining…”
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Rough fuzzy model based feature discretization in intelligent data preprocess by Chen, Qiong, Huang, Mengxing

“… Compared with other discretization methods, the discretization based on rough set has achieved good results in many applications because it can make full use of the known knowledge base without any prior information…”
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Unsupervised EA-Based Fuzzy Clustering for Image Segmentation by Zhang, Mengxuan, Jiao, Licheng, Shang, Ronghua, Zhang, Xiangrong, Li, Lingling

“…This paper presents an unsupervised fuzzy clustering based on evolutionary algorithm for image segmentation…”
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Robust semi-supervised spatial picture fuzzy clustering with local membership and KL-divergence for image segmentation by Wu, Chengmao, Zhang, Jiajia

“… Secondly, the idea of maximum entropy fuzzy clustering is introduced into picture fuzzy clustering, and an entropy-based picture fuzzy clustering with clear physical meaning is constructed…”
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Fuzzy image clustering incorporating local and region-level information with median memberships by Wang, Qingsheng, Wang, Xiaopeng, Fang, Chao, Jiao, Jianjun

“…Image segmentation with Fuzzy C-Means (FCM) clustering algorithm is a widely researched topic…”
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Adaptive safety-aware semi-supervised clustering by Gan, Haitao, Yang, Zhi, Zhou, Ran

“… To achieve the goal, we propose an adaptive safety-aware semi-supervised fuzzy c-means algorithm (AS3FCM…”
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Missing data analyses: a hybrid multiple imputation algorithm using Gray System Theory and entropy based on clustering by Tian, Jing, Yu, Bing, Yu, Dan, Ma, Shilong

“… Yet, the multiple imputation algorithms have maintained prevalent because of the further promotion of validity by minimizing the bias iteratively and less requirement on prior knowledge to the distributions…”
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The multisynapse neural network and its application to fuzzy clustering by Wei, Chih-Hsiu, Fahn, Chin-Shyurng

“… It is well known that fuzzy c-means is a milestone algorithm in the area of fuzzy c-partition clustering…”
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