Search Results - Non-iterative clustering algorithm

Non-iterative border-peeling clustering algorithm based on swap strategy

Authors: Hui Tu Shifei Ding Xiao Xu et al.

Source: Information Sciences. 654:119864

基于自然和加权共享最近邻的密度峰值聚类算法. (Chinese)

Alternate Title: Density Peak Clustering Algorithm Based on Natural and Weighted Shared Nearest Neighbors. (English)

Authors: 王 森 陈 翔 詹小秦 et al.

Source: Journal of East China Jiaotong University; Aug2025, Vol. 42 Issue 4, p120-126, 7p

Subject Terms: CLUSTERING algorithms, CENTROID, PROBABILITY density function, DATA structures

A novel approach for the segmentation of retinal images by integration K-means clustering algorithm with graph cut for image segmentation.

Authors: Bhoopalan, Ramasubramanian Priyadharshini, S.

Source: Scientific Reports; 10/15/2025, Vol. 15 Issue 1, p1-13, 13p

Subject Terms: K-means clustering, DIABETIC retinopathy, IMAGE segmentation, EDGE detection (Image processing), MEDICAL technology, IMAGE enhancement (Imaging systems), EYE examination

Stokes space modulation format classification based on non-iterative clustering algorithm for coherent optical receivers

Authors: Xiong Wu Jie Liu Mai Xiaofeng et al.

Source: Optics Express. 25:2038

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://pubmed.ncbi.nlm.nih.gov/29519052
https://www.ncbi.nlm.nih.gov/pubmed/29519052
https://www.osapublishing.org/oe/fulltext.cfm?uri=oe-25-3-2038&id=357678
https://pubmed.ncbi.nlm.nih.gov/29519052/
https://ui.adsabs.harvard.edu/abs/2017OExpr..25.2038M/abstract

Application-oriented Farsi license plate recognition using deterministic clustering algorithm and MSER detector

Authors: Mohammad Mehdi Zeinali Sedigheh Ghofrani

Source: Majlesi Journal of Electrical Engineering, Vol 10, Iss 2 (2024)

Subject Terms: OCR, law enforcement, Deterministic clustering algorithm, License plate recognition, TA1-2040, Engineering (General). Civil engineering (General)

Access URL: https://doaj.org/article/70e0a82e15da430894a33ca0533017e0

A K-Means Clustering Algorithm with Total Bregman Divergence for Point Cloud Denoising.

Authors: Duan, Xiaomin Mu, Anqi Zhao, Xinyu et al.

Source: Symmetry (20738994); Aug2025, Vol. 17 Issue 8, p1186, 21p

Subject Terms: K-means clustering, POINT cloud, SIGNAL denoising, ROBOT vision, GEOMETRIC shapes, EMPIRICAL research

Density Clustering Algorithm Based on KD-Tree and Voting Rules.

Authors: Hui Du Zhiyuan Hu Depeng Lu et al.

Source: Computers, Materials & Continua; 2024, Vol. 79 Issue 2, p3239-3259, 21p

Subject Terms: CLUSTERING algorithms, K-nearest neighbor classification, VOTING, DENSITY, ADHESIVES

S2F: Border peeling clustering from cluster skeletons to final clusters.

Authors: Zhang, Shuntai Wang, Yizhang Yang, Ming et al.

Source: Neurocomputing. Nov2025, Vol. 654, pN.PAG-N.PAG. 1p.

Subject Terms: *CLUSTERING algorithms, *K-nearest neighbor classification, *UNDIRECTED graphs, *SKELETON, *TASK performance

Automatic segmentation algorithm for high-spatial-resolution remote sensing images based on self-learning super-pixel convolutional network

Authors: Zenan Yang Haipeng Niu Liang Huang et al.

Source: International Journal of Digital Earth, Vol 15, Iss 1, Pp 1101-1124 (2022)

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, Mathematical geography. Cartography, 02 engineering and technology, deep convolution neural network model, prior entropy fuzzy c-means clustering algorithm, super-pixel algorithm, remote sensing images, GA1-1776, automatic fuzzy clustering

Access URL: https://doaj.org/article/45a02a81335a4590a41ee6d308f2e7c1

A Domain Adaptive Density Clustering Algorithm for Data With Varying Density Distribution

Authors: Jianguo Chen Philip S. Yu

Source: IEEE Transactions on Knowledge and Data Engineering. 33:2310-2321

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, Machine Learning (stat.ML), 02 engineering and technology, Machine Learning (cs.LG)

Access URL: http://arxiv.org/pdf/1911.10293
http://arxiv.org/abs/1911.10293
http://arxiv.org/pdf/1911.10293.pdf
http://ui.adsabs.harvard.edu/abs/2019arXiv191110293C/abstract
https://dblp.uni-trier.de/db/journals/tkde/tkde33.html#ChenY21
https://arxiv.org/abs/1911.10293
https://www.computer.org/csdl/journal/tk/2021/06/08906027/1f5qKGU8lSo
https://ieeexplore.ieee.org/document/8906027/
http://export.arxiv.org/pdf/1911.10293
https://arxiv.org/pdf/1911.10293v1
https://arxiv.org/abs/1911.10293

Reducing the number of centers in a probabilistic neural network via applying the first neighbor means clustering algorithm

Authors: Tetsuya Hoya

Source: Array, Vol 14, Iss , Pp 100161- (2022)

Subject Terms: Radial basis function networks, Probabilistic neural network, Center selection, Modified FINCH algorithm, First neighbor means clustering, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2590005622000273; https://doaj.org/toc/2590-0056

Access URL: https://doaj.org/article/4ab79e28d8f24ba9bc579ca243d46454

A novel density peak clustering algorithm based on squared residual error

Authors: PARMAR, Milan WANG, Di TAN, Ah-hwee et al.

Contributors: PARMAR, Milan WANG, Di TAN, Ah-hwee et al.

Source: 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). :43-48

Subject Terms: Engineering::Computer science and engineering [DRNTU], low-density data points, Databases and Information Systems, Theory and Algorithms, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, density peak clustering, Density Peak Clustering, Clustering, clustering, squared residual error

File Description: application/pdf

Access URL: https://dr.ntu.edu.sg/bitstream/10356/89594/1/SPAC2017C.pdf
https://ink.library.smu.edu.sg/sis_research/5465/
https://dr.ntu.edu.sg/handle/10220/47062
https://dr.ntu.edu.sg/bitstream/10356/89594/1/SPAC2017C.pdf
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6468&context=sis_research
https://dblp.uni-trier.de/db/conf/spac/spac2017.html#ParmarWTMJZ17
http://hdl.handle.net/10220/47062
https://hdl.handle.net/10356/89594

基于RF分类调优和SNIC 聚类的新疆红枣 种植区遥感提取. (Chinese)

Alternate Title: Remote sensing extraction of jujube planting area in Xinjiang based on RF classification optimization and SNIC clustering. (English)

Authors: 赵国兵 郑江华 王蕾 et al.

Source: Arid Land Geography; Jun2024, Vol. 47 Issue 6, p1004-1014, 11p

Subject Terms: JUJUBE (Plant), AGRICULTURAL modernization, REGIONAL development, RANDOM forest algorithms, DATA mining

一种改进的SAR图像舰船目标超像素 快速检测算法. (Chinese)

Alternate Title: An Improved Superpixel Fast Detection Algorithm for Ship Target in SAR Images. (English)

Authors: 李雨轩 刘 峥 冉 磊

Source: Journal of Signal Processing; Jan2025, Vol. 41 Issue 1, p113-126, 14p

A Domain Adaptive Density Clustering Algorithm for Data with Varying Density Distribution

Authors: Chen, Jianguo Yu, Philip S.

Index Terms: Computer Science - Machine Learning, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/1911.10293

A Domain Adaptive Density Clustering Algorithm for Data With Varying Density Distribution.

Authors: Chen, Jianguo Yu, Philip S.

Source: IEEE Transactions on Knowledge & Data Engineering; Jun2021, Vol. 33 Issue 6, p2310-2321, 12p

Subject Terms: DATA mining, DENSITY, COMPUTATIONAL complexity

Robust superpixel-based fuzzy possibilistic clustering method incorporating local information for image segmentation.

Authors: Wu, Chengmao Zhao, Jingtian

Source: Visual Computer; Nov2024, Vol. 40 Issue 11, p7961-8000, 40p

Subject Terms: IMAGE segmentation, COMPUTATIONAL complexity, SEARCH algorithms, ALGORITHMS, FUZZY algorithms, PIXELS

Density Peaks Clustering Algorithm Based on a Divergence Distance and Tissue—Like P System.

Authors: Ge, Fuhua Liu, Xiyu

Source: Applied Sciences (2076-3417); Feb2023, Vol. 13 Issue 4, p2293, 19p

Subject Terms: SPECIFIC gravity, DENSITY, EUCLIDEAN distance, ALGORITHMS, TISSUES

Enhanced Short-Term Residential Load Forecasting Using Kmeans Clustering and Iterative Residual LSTM Networks.

Authors: Sulaiman, Abdullahi Abdullateef, Ayodele Isqeel Issa, Abdulkabir Olatunji et al.

Source: Computer Engineering & Applications Journal; Feb2025, Vol. 14 Issue 1, p22-39, 18p

Subject Terms: K-means clustering, LONG short-term memory, DEMAND forecasting, ESTIMATION theory, SEASONAL temperature variations, DEEP learning, ENERGY consumption forecasting, ENERGY management

Simple non-iterative clustering and CNNs for coarse segmentation of breast cancer whole-slide images

Authors: Muhammad Shaban Jane E. Armes Fayyaz ul Amir Afsar Minhas et al.

Source: Medical Imaging 2021: Digital Pathology. :15

Subject Terms: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

Access URL: https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11603/116030I/Simple-non-iterative-clustering-and-CNNs-for-coarse-segmentation-of/10.1117/12.2581978.full
http://ui.adsabs.harvard.edu/abs/2021SPIE11603E..0IA/abstract