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Efficient global clustering using the Greedy Elimination MethodCHAN, Z. S. H; KASABOV, N.Electronics Letters. 2004, Vol 40, Num 25, pp 1611-1612, issn 0013-5194, 2 p.Article

Regional and online learnable fieldsSCHATTEN, Rolf; GOERKE, N. Rolf; ECKMILLER, Rolf et al.International Joint Conference on Neural Networks. 2004, isbn 0-7803-8359-1, 4Vol, Vol1, 793-798Conference Paper

Construction of Small World Networks Based on K-Means Clustering AnalysisJIANYU LI; RUI LV; ZHANXIN YANG et al.Lecture notes in computer science. 2006, pp 997-1000, issn 0302-9743, isbn 3-540-34379-2, 4 p.Conference Paper

Fast global k-means with similarity functions algorithmLOPEZ-ESCOBAR, Saul; CARRASCO-OCHOA, J. A; MARTINEZ-TRINIDAD, J. Fco et al.Lecture notes in computer science. 2006, pp 512-521, issn 0302-9743, isbn 3-540-45485-3, 1Vol, 10 p.Conference Paper

T-REKS: identification of Tandem REpeats in sequences with a K-meanS based algorithmJORDA, Julien; KAJAVA, Andrey V.Bioinformatics (Oxford. Print). 2009, Vol 25, Num 20, pp 2632-2638, issn 1367-4803, 7 p.Article

A group quorum system of degree 1 + √1+n mCHEDID, Fouad B.Lecture notes in computer science. 2006, pp 70-81, issn 0302-9743, isbn 978-3-540-68139-7, 1Vol, 12 p.Conference Paper

A method for initialising the K-means clustering algorithm using kd-treesREDMOND, Stephen J; HENEGHAN, Conor.Pattern recognition letters. 2007, Vol 28, Num 8, pp 965-973, issn 0167-8655, 9 p.Article

Automated variable weighting in k-means type clusteringJOSHUA ZHEXUE HUANG; NG, Michael K; HONGQIANG RONG et al.IEEE transactions on pattern analysis and machine intelligence. 2005, Vol 27, Num 5, pp 657-668, issn 0162-8828, 12 p.Article

Molecular dynamics-like data clustering approachLI JUNLIN; FU HONGGUANG.Pattern recognition. 2011, Vol 44, Num 8, pp 1721-1737, issn 0031-3203, 17 p.Article

Super-cooled Droplet Splash Image ClassificationXUEQING ZHANG; BARNES, Stuart; SHAN FU et al.Proceedings of SPIE, the International Society for Optical Engineering. 2009, Vol 7375, issn 0277-786X, isbn 978-0-8194-7651-7 0-8194-7651-X, 73752F.1-73752F.8, 2Conference Paper

How slow is the k-means method?ARTHUR, David; VASSILVITSK, Sergei.SCG : symposium on computational geometry. 2006, pp 144-153, isbn 1-59593-340-9, 1Vol, 10 p.Conference Paper

Document clustering with grouping and chaining algorithmsCHALI, Yllias; NOUREDDINE, Soufiane.Lecture notes in computer science. 2005, pp 280-291, issn 0302-9743, isbn 3-540-29172-5, 1Vol, 12 p.Conference Paper

Outliers in rough k-means clusteringPETERS, Georg.Lecture notes in computer science. 2005, pp 702-707, issn 0302-9743, isbn 3-540-30506-8, 1Vol, 6 p.Conference Paper

Regional and online learnable fieldsSCHATTEN, Rolf; GOERKE, Nils; ECKMILLER, Rolf et al.Lecture notes in computer science. 2005, issn 0302-9743, isbn 3-540-28757-4, 2Vol, Part II, 74-83Conference Paper

A revision for Gaussian mixture density decomposition algorithmXIAOBING YANG; FANSHENG KONG; BIHONG LIU et al.Lecture notes in computer science. 2004, pp 1014-1019, issn 0302-9743, isbn 3-540-24127-2, 6 p.Conference Paper

Cross-entropy clusteringTABOR, J; SPUREK, P.Pattern recognition. 2014, Vol 47, Num 9, pp 3046-3059, issn 0031-3203, 14 p.Article

Improvement of neural network classifier using floating centroidsLIN WANG; BO YANG; YUEHUI CHEN et al.Knowledge and information systems (Print). 2012, Vol 31, Num 3, pp 433-454, issn 0219-1377, 22 p.Article

SLIC Superpixels Compared to State-of-the-Art Superpixel MethodsACHANTA, Radhakrishna; SHAJI, Appu; SMITH, Kevin et al.IEEE transactions on pattern analysis and machine intelligence. 2012, Vol 34, Num 11, pp 2274-2281, issn 0162-8828, 8 p.Article

Research on Determining the Weights of Urban Land Grading Evaluation Factors Based on Spearman Rank Correlation AnalysisWEI WANG; WEI QI; NENGCHENG CHEN et al.Proceedings of SPIE, the International Society for Optical Engineering. 2009, Vol 7492, issn 0277-786X, isbn 978-0-8194-7803-0 0-8194-7803-2, 74921U.1-74921U.10, 3Conference Paper

Improving K-means by outlier removalHAUTAMÄKI, Ville; CHEREDNICHENKO, Svetlana; KÄRKKÄINEN, Ismo et al.Lecture notes in computer science. 2005, pp 978-987, issn 0302-9743, isbn 3-540-26320-9, 10 p.Conference Paper

Self-organizing maps as substitutes for K-means clusteringBACAO, Fernando; LOBO, Victor; PAINHO, Marco et al.Lecture notes in computer science. 2005, issn 0302-9743, isbn 3-540-26032-3, 3Vol, part III, 476-483Conference Paper

A new cluster validity measure and its application to image compressionCHOU, C.-H; SU, M.-C; LAI, E et al.Pattern analysis and applications (Print). 2004, Vol 7, Num 2, pp 205-220, issn 1433-7541, 16 p.Article

Automatically finding clusters in normalized cutsTEPPER, Mariano; MUSE, Pablo; ALMANSA, Andres et al.Pattern recognition. 2011, Vol 44, Num 7, pp 1372-1386, issn 0031-3203, 15 p.Article

Conceptual K-means algorithm based on complex featuresAYAQUICA-MARTINEZ, I. O; MARTINEZ-TRINIDAD, J. Fco; CARRASCO-OCHOA, J. Ariel et al.Lecture notes in computer science. 2006, pp 491-501, issn 0302-9743, isbn 3-540-46556-1, 1Vol, 11 p.Conference Paper

Genetic algorithm-based clustering and its new mutation operatorTHAMMANO, Arit; KAKULPHIMP, Uraiwan.Lecture notes in computer science. 2006, pp 703-708, issn 0302-9743, isbn 3-540-37271-7, 6 p.Conference Paper

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