14.2.15 Fuzzy Clustering, Fuzzy Classification Techniques, Fuzzy C-Means

Chapter Contents (Back)
Fuzzy Clustering. Clustering. C-Means Clustering. Each data point belongs to a cluster to some degree (i.e. fuzzy membership). So has a rating for multiple clusters.
See also Fuzzy Sets, Fuzzy Logic.

Gu, T., and Dubuisson, B.,
A Loose-Pattern Process Approach to Clustering Fuzzy Data Sets,
PAMI(7), No. 3, May 1985, pp. 366-372. BibRef 8505

Hathaway, R.J.[Richard J.], Bezdek, J.C.[James C.],
Local convergence of the fuzzy c-Means algorithms,
PR(19), No. 6, 1986, pp. 477-480.
Elsevier DOI 0309

Hathaway, R.J.[Richard J.], Bezdek, J.C.[James C.], Davenport, J.W.[John W.],
On Relational Data Versions of C-Means Algorithms,
PRL(17), No. 6, May 15 1996, pp. 607-612. 9607

Hathaway, R.J.[Richard J.], Davenport, J.W.[John W.], Bezdek, J.C.[James C.],
Relational duals of the C-means clustering algorithms,
PR(22), No. 2, 1989, pp. 205-212.
Elsevier DOI 0309

Hathaway, R.J.[Richard J.], Bezdek, J.C.[James C.],
Nerf c-means: Non-Euclidean relational fuzzy clustering,
PR(27), No. 3, March 1994, pp. 429-437.
Elsevier DOI 0401

Hathaway, R.J.[Richard J.], Bezdek, J.C.[James C.],
Clustering incomplete relational data using the non-Euclidean relational fuzzy c-means algorithm,
PRL(23), No. 1-3, January 2002, pp. 151-160.
Elsevier DOI 0201

Cannon, R.L., Dave, J.V., and Bezdek, J.C.,
Efficient Implementation of the Fuzzy C-Means Clustering Algorithm,
PAMI(8), No. 2, March 1986, pp. 248-255. BibRef 8603

Tsao, E.C.K.[Eric Chen-Kuo], Bezdek, J.C.[James C.], Pal, N.R.[Nikhil R.],
Fuzzy Kohonen clustering networks,
PR(27), No. 5, May 1994, pp. 757-764.
Elsevier DOI 0401

Cannon, R.L.[Robert L.], Dave, J.V.[Jitendra V.], Bezdek, J.C.[James C.], and Trivedi, M.M.[Mohan M.],
Segmentation of a Thematic Mapper Image Using the Fuzzy C-Means Clustering Algorithms,
GeoRS(24), No. 3, May 1986, pp. 400-408.
IEEE Top Reference. BibRef 8605

Trivedi, M.M.[Mohan M.], and Bezdek, J.C.[James C.],
Low-level Segmentation of Aerial Images Using Fuzzy Clustering,
SMC(16), No. 4, July 1986, pp. 589- 598. BibRef 8607

Ismail, M.A., Selim, S.Z.[Shokri Z.],
Fuzzy C-Means: Optimality of solutions and effective termination of the algorithm,
PR(19), No. 6, 1986, pp. 481-485.
Elsevier DOI 0309

See also K-Means-Type Algorithms: A Generalized Convergence Theorem and Characterization of Local Optimality.
See also On the Local Optimality of the Fuzzy ISODATA Clustering Algorithm. BibRef

Selim, S.Z.[Shokri Z.], Ismail, M.A.,
Soft clustering of multidimensional data: a semi-fuzzy approach,
PR(17), No. 5, 1984, pp. 559-568.
Elsevier DOI 0309

Selim, S.Z.[Shokri Z.],
Comments on: optimality test for fixed points,
PR(23), No. 11, 1990, pp. 1307-1308.
Elsevier DOI 0401

See also Optimality tests for fixed points of the fuzzy c-means algorithm. BibRef

Kamel, M.S.[Mohamed S.], Selim, S.Z.[Shokri Z.],
New algorithms for solving the fuzzy clustering problem,
PR(27), No. 3, March 1994, pp. 421-428.
Elsevier DOI 0401

Kamel, M.S.[Mohamed S.], Selim, S.Z.[Shokri Z.],
A thresholded fuzzy c-means algorithm for semi-fuzzy clustering,
PR(24), No. 9, 1991, pp. 825-833.
Elsevier DOI 0401

Al-Sultan, K.S.[Khaled S.], Selim, S.Z.[Shokri Z.],
A global algorithm for the fuzzy clustering problem,
PR(26), No. 9, September 1993, pp. 1357-1361.
Elsevier DOI 0401

See also Tabu search approach to the clustering problem, A. BibRef

Kent, J.T., and Mardia, K.V.,
Spatial Classification Using Fuzzy Membership Models,
PAMI(10), No. 5, September 1988, pp. 659-671.
IEEE DOI BibRef 8809

Lopez de Mantaras, R., and Valverde, L.,
New Results in Fuzzy Clustering Based on the Concept of Indistinguishability Relation,
PAMI(10), No. 5, September 1988, pp. 754-757.
IEEE DOI BibRef 8809

Gath, I., and Geva, A.B.,
Unsupervised Optimal Fuzzy Clustering,
PAMI(11), No. 7, July 1989, pp. 773-780.
IEEE DOI BibRef 8907

Policker, S., Geva, A.B.,
A New Algorithm for Time Series Prediction by Temporal Fuzzy Clustering,
ICPR00(Vol II: 728-731).

Babu, G.P.[G. Phanendra], Murty, M.N.[M. Narasimha],
Clustering with evolution strategies,
PR(27), No. 2, February 1994, pp. 321-329.
Elsevier DOI 0401

Asharaf, S., Murty, M.N.[M. Narasimha],
An adaptive rough fuzzy single pass algorithm for clustering large data sets,
PR(36), No. 12, December 2003, pp. 3015-3018.
Elsevier DOI 0310

Asharaf, S., Murty, M.N.[M. Narasimha], Shevade, S.K.,
Rough set based incremental clustering of interval data,
PRL(27), No. 6, 15 April 2006, pp. 515-519.
Elsevier DOI 0604
Clustering; Leader; Interval data; Rough set
See also Rough support vector clustering. BibRef

Lenart, C.[Cristian],
Defining separability of two fuzzy clusters by a fuzzy decision hyperplane,
PR(26), No. 9, September 1993, pp. 1351-1356.
Elsevier DOI 0401

Marsililibelli, S., Muller, A.,
Adaptive Fuzzy Pattern-Recognition in the Anaerobic-Digestion Process,
PRL(17), No. 6, May 15 1996, pp. 651-659. 9607

Bandemer, H.,
Specifying Fuzzy Data from Grey-Tone Pictures for Pattern-Recognition,
PRL(17), No. 6, May 15 1996, pp. 585-592. 9607
And: Correction: PRL(17), No. 13, November 25 1996, pp. 1413-1413. BibRef

Beni, G., Liu, X.M.,
A Least Biased Fuzzy Clustering Method,
PAMI(16), No. 9, September 1994, pp. 954-960.
IEEE DOI BibRef 9409

Man, Y., Gath, I.,
Detection and Separation of Ring-Shaped Clusters Using Fuzzy Clustering,
PAMI(16), No. 8, August 1994, pp. 855-861.
IEEE DOI BibRef 9408

Cai, Y.Y., Loh, H.T., Nee, A.Y.C.,
Qualitative Primitive Identification Using Fuzzy Clustering and Invariant Approach,
IVC(14), No. 7, July 1996, pp. 451-464.
Elsevier DOI 9607

Chen, N.X., Bedrosian, S.D.,
Effect of Fuzzy Membership on Recognition of Gray Level Images,
PRL(4), 1986, pp. 443-447. BibRef 8600

Binaghi, E., Madella, P., Montesano, M.G., Rampini, A.,
Fuzzy Contextual Classification of Multisource Remote Sensing Images,
GeoRS(35), No. 2, March 1997, pp. 326-340.
IEEE Top Reference. 9704

Binaghi, E., Gallo, I., Pepe, M.,
A cognitive pyramid for contextual classification of remote sensing images,
GeoRS(41), No. 12, December 2003, pp. 2906-2922.
IEEE Abstract. 0402

Gallo, I.[Ignazio], Binaghi, E.[Elisabetta],
Information Extraction and Classification from Free Text Using a Neural Approach,
Springer DOI 0711

Gath, I., Iskoz, A.S., Vancutsem, B.,
Data Induced Metric and Fuzzy Clustering of Nonconvex Patterns of Arbitrary Shape,
PRL(18), No. 6, June 1997, pp. 541-553. 9710

Mannan, B., Roy, J., Ray, A.K.,
Fuzzy Artmap Supervised Classification of Multispectral Remotely Sensed Images,
JRS(19), No. 4, March 10 1998, pp. 767-774. 9803

Tolias, Y.A., Panas, S.M.,
Image Segmentation by a Fuzzy Clustering-Algorithm Using Adaptive Spatially Constrained Membership Functions,
SMC-A(28), No. 3, May 1998, pp. 359-369.
IEEE Top Reference. 9805

See also Fuzzy Vessel Tracking Algorithm for Retinal Images Based on Fuzzy Clustering, A. BibRef

Mari, M., Dellepiane, S.G.,
A Nonlinear Image Processing Approach Through Fuzzy Measures,
PRL(18), No. 11-13, November 1997, pp. 1109-1115. 9806

Dellepiane, S.G., Fontana, F., Vernazza, G.L.,
Nonlinear Image Labeling for Multivalued Segmentation,
IP(5), No. 3, March 1996, pp. 429-446.
IEEE DOI BibRef 9603

Israel, S.A., Kasabov, N.K.,
Statistical, Connectionist, and Fuzzy Inference Techniques for Image Classification,
JEI(6), No. 3, July 1997, pp. 337-347. 9807

Boninsegna, M., Coianiz, T., Trentin, E.,
Estimating the Crowding Level with a Neuro-Fuzzy Classifier,
JEI(6), No. 3, July 1997, pp. 319-328. 9807

Cheung, K.F.,
Fuzzy One-Mean Algorithm: Formulation, Convergence Analysis, and Applications,
JIFS(5), No. 4, 1997, pp. 323-332. 9809

Somasundaram, A., Somasundaram, S.,
Domination in Fuzzy Graphs: I,
PRL(19), No. 9, 31 July 1998, pp. 787-791. BibRef 9807

Singh, S.[Sameer],
Effect of noise on generalisation in massively parallel fuzzy systems,
PR(31), No. 11, November 1998, pp. 1767-1775.
Elsevier DOI BibRef 9811

Wu, P.S.[Paul S.], Li, M.[Ming],
Supervised and unsupervised fuzzy-adaptive Hamming net,
PR(32), No. 10, October 1999, pp. 1801-1816.
Elsevier DOI BibRef 9910

Singh, S.,
A Single Nearest Neighbor Fuzzy Approach for Pattern Recognition,
PRAI(13), No. 1, February 1999, pp. 49. BibRef 9902

Dinda, T.K.[Tapan K.], Ray, K.S.[Kumar S.], Chakraborty, M.K.[Mihir K.],
Fuzzy relational calculus approach to multidimensional pattern classification,
PR(32), No. 6, June 1999, pp. 973-995.
Elsevier DOI BibRef 9906

Ray, K.S., Dinda, T.K.,
Pattern classification using fuzzy relational calculus,
SMC-B(33), No. 1, February 2003, pp. 1-16.
IEEE Top Reference. 0301

Melgani, F., Al Hashemy, B.A.R., Taha, S.M.R.,
An Explicit Fuzzy Supervised Classification Method for Multispectral Remote Sensing Images,
GeoRS(38), No. 1, January 2000, pp. 287-295.
IEEE Top Reference. 0002

Alonso-Betanzos, A.[Amparo], Arcay-Varela, B.[Bernardino], Castro-Martínez, A.[Alfonso],
Analysis and evaluation of hard and fuzzy clustering segmentation techniques in burned patient images,
IVC(18), No. 13, October 2000, pp. 1045-1054.
Elsevier DOI 0008

Castro, A.[Alfonso], Bóveda, C.[Carmen], Rey, A.[Alberto], Arcay, B.[Bernardino],
An Analysis of Different Clustering Algorithms for ROI Detection in High Resolutions CT Lung Images,
ICCVG10(I: 241-248).
Springer DOI 1009

Castro-Martínez, A.[Alfonso], Bóveda, C.[Carmen], Arcay, B.[Bernardino],
Analysis of Fuzzy Clustering Algorithms for the Segmentation of Burn Wounds Photographs,
ICIAR06(II: 491-501).
Springer DOI 0610

Ménard, M.[Michel], Demko, C.[Christophe], Loonis, P.[Pierre],
The fuzzy C+2-Means: solving the ambiguity rejection in clustering,
PR(33), No. 7, July 2000, pp. 1219-1237.
Elsevier DOI 0005

Liew, A.W.C.[Alan Wee-Chung], Leung, S.H., Lau, W.H.,
Fuzzy image clustering incorporating spatial continuity,
VISP(147), No. 2, April 2000, pp. 185. 0005

Ozols, J., Borisov, A.,
Fuzzy classification based on pattern projections analysis,
PR(34), No. 4, April 2001, pp. 763-781.
Elsevier DOI 0101

Martínez Trinidad, J.F.[José Francisco], Ruiz Shulcloper, J.[José],
Fuzzy clustering of semantic spaces,
PR(34), No. 4, April 2001, pp. 783-793.
Elsevier DOI 0101

Seong, J.C.[Jeong Chang], Usery, E.L.[E. Lynn],
Fuzzy Image Classification for Continental-Scale Multitemporal NDVI Series Images Using Invariant Pixels and an Image Stratification Method,
PhEngRS(67), No. 3, March 2001, pp. 287-294. Use invariant pixels for land-cover classification with NDVI images covering a large area to provide ground-truth data. 0102

Palshikar, G.K.[Girish Keshav],
A fuzzy temporal notation and its application to specify fault patterns for diagnosis,
PRL(22), No. 3-4, March 2001, pp. 381-394.
Elsevier DOI 0105
Classification. BibRef

Quek, C., Tung, W.L.,
A novel approach to the derivation of fuzzy membership functions using the Falcon-MART architecture,
PRL(22), No. 9, July 2001, pp. 941-958.
Elsevier DOI 0106

Quah, K.H., Quek, C., Leedham, G.,
Reinforcement learning combined with a fuzzy adaptive learning control network (FALCON-R) for pattern classification,
PR(38), No. 4, April 2005, pp. 513-526.
Elsevier DOI 0501

Hsu, Y.C.[Ya-Chen], Chen, G.R.[Guan-Rong], Li, H.X.[Han-Xiong],
A fuzzy adaptive variable structure controller with applications to robot manipulators,
SMC-B(31), No. 3, June 2001, pp. 331-340.
IEEE Top Reference. 0108

Ramot, D., Milo, R., Friedman, M., Kandel, A.,
On fuzzy correlations,
SMC-B(31), No. 3, June 2001, pp. 381-390.
IEEE Top Reference. 0108

Schenker, A.[Adam], Last, M.[Mark], Bunke, H.[Horst], Kandel, A.[Abraham],
Fuzzy Clustering With Genetically Adaptive Scaling,
IJIG(2), No. 4, October 2002, pp. 557-572. 0210

Pascual-Marqui, R.D., Pascual-Montano, A.D., Kochi, K., Carazo, J.M.,
Smoothly distributed fuzzy C-means: a new self-organizing map,
PR(34), No. 12, December 2001, pp. 2395-2402.
Elsevier DOI 0110
A New Self-organizing Map Based on Smoothly Distributed Fuzzy C-means,
ICPR00(Vol II: Not in proceedings). 0009

Yu, S.X.[Shi-Xin], de Backer, S.[Steve], Scheunders, P.[Paul],
Genetic feature selection combined with composite fuzzy nearest neighbor classifiers for hyperspectral satellite imagery,
PRL(23), No. 1-3, January 2002, pp. 183-190.
Elsevier DOI 0201

Yager, R.R.,
Using fuzzy methods to model nearest neighbor rules,
SMC-B(32), No. 4, August 2002, pp. 512-525.
IEEE Top Reference. 0207

Yager, R.R., and Filev, D.P.,
Approximate Clustering via the Mountain Method,
SMC(24), No. 8, 1994, pp. 1279-1284. BibRef 9400

Yager, R.R., and Filev, D.P.,
Generation of Fuzzy Rules by Mountain Clustering,
JIFS(2), 1994, pp. 209-219. BibRef 9400

Rickard, J.T., Yager, R.R., Miller, W.,
Mountain Clustering on Non-Uniform Grids Using P-Trees,
FuzzyOpt(4), No. 2, April 2005, pp. 87-102.
Springer DOI BibRef 0504
Mountain clustering on nonuniform grids,

Belacel, N.[Nabil], Hansen, P.[Pierre], Mladenovic, N.[Nenad],
Fuzzy J-Means: a new heuristic for fuzzy clustering,
PR(35), No. 10, October 2002, pp. 2193-2200.
Elsevier DOI 0206

La Plante, F.[François], Kardouchi, M.[Mustapha], Belacel, N.[Nabil],
Image Categorization Using a Heuristic Automatic Clustering Method Based on Hierarchical Clustering,
Springer DOI 1507

Wu, K.L.[Kuo-Lung], Yang, M.S.[Miin-Shen],
Alternative c-means clustering algorithms,
PR(35), No. 10, October 2002, pp. 2267-2278.
Elsevier DOI 0206
New metric to replace the Euclidean norm in c-means clustering procedures.
See also Mean shift-based clustering. BibRef

Yang, M.S.[Miin-Shen], Wu, K.L.[Kuo-Lung],
A similarity-based robust clustering method,
PAMI(26), No. 4, April 2004, pp. 434-448.
IEEE Abstract. 0403
Robust to initialization, robust to cluster volumes, robust to noise and outliers. Alternating optimization procedure. BibRef

Wu, K.L.[Kuo-Lung], Yang, M.S.[Miin-Shen],
A cluster validity index for fuzzy clustering,
PRL(26), No. 9, 1 July 2005, pp. 1275-1291.
Elsevier DOI 0506

Wu, K.L.[Kuo-Lung],
Analysis of parameter selections for fuzzy c-means,
PR(45), No. 1, 2012, pp. 407-415.
Elsevier DOI 1410
Fuzzy clustering BibRef

Shen, Q.A.[Qi-Ang], Chouchoulas, A.[Alexios],
Combining rough sets and data-driven fuzzy learning for generation of classification rules,
PR(32), No. 12, December 1999, pp. 2073-2076.
Elsevier DOI BibRef 9912

Shen, Q.A.[Qi-Ang], Chouchoulas, A.[Alexios],
A rough-fuzzy approach for generating classification rules,
PR(35), No. 11, November 2002, pp. 2425-2438.
Elsevier DOI 0208

Kong, X.W.[Xiang-Wei], Wang, R.Y.[Ren-Ying], Li, G.P.[Guo-Ping],
Fuzzy clustering algorithms based on resolution and their application in image compression,
PR(35), No. 11, November 2002, pp. 2439-2444.
Elsevier DOI 0208

Zhang, M.R.[Ming-Rui], Hall, L.O.[Lawrence O.], Goldgof, D.B.[Dmitry B.],
A generic knowledge-guided image segmentation and labeling system using fuzzy clustering algorithms,
SMC-B(32), No. 5, October 2002, pp. 571-582.
IEEE Top Reference. 0210

See also scalable framework for cluster ensembles, A. BibRef

Clark, M.C., Hall, L.O., Li, C.L.[Chun-Lin], Goldgof, D.B.,
Knowledge based (re-)clustering,

Hu, Y.C.[Yi-Chung], Chen, R.S.[Ruey-Shun], Tzeng, G.H.[Gwo-Hshiung],
Finding fuzzy classification rules using data mining techniques,
PRL(24), No. 1-3, January 2003, pp. 509-519.
Elsevier DOI 0211

Fan, J.L.[Jiu-Lun], Zhen, W.Z.[Wen-Zhi], Xie, W.X.[Wei-Xin],
Suppressed fuzzy c-means clustering algorithm,
PRL(24), No. 9-10, June 2003, pp. 1607-1612.
Elsevier DOI 0304

Aidarkhanov, M.B., La, L.L.,
On stability of group fuzzy classification algorithms,
PRL(24), No. 12, August 2003, pp. 1921-1924.
Elsevier DOI 0304

Abonyi, J.[Janos], Szeifert, F.[Ferenc],
Supervised fuzzy clustering for the identification of fuzzy classifiers,
PRL(24), No. 14, October 2003, pp. 2195-2207.
Elsevier DOI 0307

Liu, H.[Hong], Huang, S.T.[Shang-Teng],
Evolutionary semi-supervised fuzzy clustering,
PRL(24), No. 16, December 2003, pp. 3105-3113.
Elsevier DOI 0310

Shackelford, A.K., Davis, C.H.,
A hierarchical fuzzy classification approach for high-resolution multispectral data over urban areas,
GeoRS(41), No. 9, September 2003, pp. 1920-1932.
IEEE Abstract. 0310

Shackelford, A.K., Davis, C.H.,
A combined fuzzy pixel-based and object-based approach for classification of high-resolution multispectral data over urban areas,
GeoRS(41), No. 10, October 2003, pp. 2354-2364.
IEEE Abstract. 0310

Kim, D.W.[Dae-Won], Lee, K.H.[Kwang H.], Lee, D.[Doheon],
A novel initialization scheme for the fuzzy c-means algorithm for color clustering,
PRL(25), No. 2, January 2004, pp. 227-237.
Elsevier DOI 0401

Zhang, D.Q.[Dao-Qiang], Chen, S.C.[Song-Can],
A comment on 'Alternative c-means clustering algorithms',
PR(37), No. 2, February 2004, pp. 173-174.
Elsevier DOI 0311

See also Alternative c-means clustering algorithms. BibRef

Cinque, L., Foresti, G.L., Lombardi, L.,
A clustering fuzzy approach for image segmentation,
PR(37), No. 9, September 2004, pp. 1797-1807.
Elsevier DOI 0407

Cinque, L., Foresti, G.L., Gumina, A., Levialdi, S.,
A modified fuzzy ART for image segmentation,

Wang, X.Z.[Xi-Zhao], Wang, Y.D.[Ya-Dong], Wang, L.J.[Li-Juan],
Improving Fuzzy C-Means Clustering Based on Feature-Weight Learning,
PRL(25), No. 10, 16 July 2004, pp. 1123-1132.
Elsevier DOI 0407

See also Improving Performance of Similarity-Based Clustering by Feature Weight Learning. BibRef

Kim, D.W.[Dae-Won], Lee, K.H.[Kwang H.], Lee, D.[Doheon],
Fuzzy clustering of categorical data using fuzzy centroids,
PRL(25), No. 11, August 2004, pp. 1263-1271.
Elsevier DOI 0409
Extend to fuzzy centroids. BibRef

Chang, X., Lilly, J.H.,
Evolutionary Design of a Fuzzy Classifier From Data,
SMC-B(34), No. 4, August 2004, pp. 1894-1906.
IEEE Abstract. 0409

Mitra, S.[Sushmita],
An evolutionary rough partitive clustering,
PRL(25), No. 12, September 2004, pp. 1439-1449.
Elsevier DOI 0409
Evolutionary C-Means clustering. BibRef

Zhang, D.Q.[Dao-Qiang], Chen, S.C.[Song-Can],
Robust Image Segmentation Using FCM With Spatial Constraints Based on New Kernel-Induced Distance Measure,
SMC-B(34), No. 4, August 2004, pp. 1907-1916.
IEEE Abstract. 0409
(FCM: Fuzzy C-Means Clustering). BibRef

Zhang, D.Q.[Dao-Qiang], Chen, S.C.[Song-Can], Zhou, Z.H.[Zhi-Hua],
Learning the kernel parameters in kernel minimum distance classifier,
PR(39), No. 1, January 2006, pp. 133-135.
Elsevier DOI 0512

di Gesù, V.[Vito], lo Bosco, G.[Giosuè],
A genetic integrated fuzzy classifier,
PRL(26), No. 4, March 2005, pp. 411-420.
Elsevier DOI 0501

Yu, J., Yang, M.S.,
A Note on the ICS Algorithm With Corrections and Theoretical Analysis,
IP(14), No. 7, July 2005, pp. 973-978.
intercluster separation fuzzy clustering. Point out errors in ICS algorithm of
See also Fuzzy algorithms for combined quantization and dithering. and show corrections. BibRef

Bhatt, R.B.[Rajen B.], Gopal, M.,
On fuzzy-rough sets approach to feature selection,
PRL(26), No. 7, 15 May 2005, pp. 965-975.
Elsevier DOI 0506

Bhatt, R.B.[Rajen B.], Gopal, M.,
On the compact computational domain of fuzzy-rough sets,
PRL(26), No. 11, August 2005, pp. 1632-1640.
Elsevier DOI 0506

Bhatt, R.B.[Rajen B.], Gopal, M.,
On the extension of functional dependency degree from crisp to fuzzy partitions,
PRL(27), No. 5, 1 April 2006, pp. 487-491.
Elsevier DOI Dependency degree; Fuzzy-rough sets; Rough sets 0604

Alexiuk, M.D.[Mark D.], Pizzi, N.J.[Nicolino J.],
Robust centroids using fuzzy clustering with feature partitions,
PRL(26), No. 8, June 2005, pp. 1039-1046.
Elsevier DOI 0506

de Cáceres, M.[Miquel], Oliva, F.[Francesc], Font, X.[Xavier],
On relational possibilistic clustering,
PR(39), No. 11, November 2006, pp. 2010-2024.
Elsevier DOI 0608
Cluster analysis; Possibilistic c-means; Relational data; Dissimilarity measures BibRef

Cai, W.L.[Wei-Ling], Chen, S.C.[Song-Can], Zhang, D.Q.[Dao-Qiang],
Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation,
PR(40), No. 3, March 2007, pp. 825-838.
Elsevier DOI 0611
Award, Pattern Recognition, Honorable Mention. Fuzzy c-means clustering (FCM); Enhanced fuzzy c-means clustering; Image segmentation; Robustness; Spatial constraints; Gray constraints; Fast clustering BibRef

Cai, W.L.[Wei-Ling], Chen, S.C.[Song-Can], Zhang, D.Q.[Dao-Qiang],
A simultaneous learning framework for clustering and classification,
PR(42), No. 7, July 2009, pp. 1248-1259.
Elsevier DOI 0903
Structure in data; Bayesian theory; Clustering learning; Classification learning; Simultaneous classification and clustering learning BibRef

de Carvalho, F.A.T.[Francisco A.T.],
Fuzzy c-means clustering methods for symbolic interval data,
PRL(28), No. 4, 1 March 2007, pp. 423-437.
Elsevier DOI 0701
Symbolic data analysis; Fuzzy c-means clustering methods; Symbolic interval data; Squared euclidean distances; Adaptive distances; Fuzzy partition interpretation indices; Fuzzy cluster interpretation indices BibRef

Dai, S.S.[Shuang-Shuang], Dhawan, A.P.[Atam P.],
Adaptive learning for event modeling and characterization,
PR(40), No. 5, May 2007, pp. 1544-1555.
Elsevier DOI 0702
Hierarchical clustering; Fuzzy k-means clustering; Adaptive learning; Event modeling BibRef

Hu, Y.K., Hu, Y.P.,
Global optimization in clustering using hyperbolic cross points,
PR(40), No. 6, June 2007, pp. 1722-1733.
Elsevier DOI 0704
Clustering; Fuzzy c-means; Hard c-means; Global optimization; Hyperbolic cross points; Genetic algorithms BibRef

Zhou, E.W.[En-Wang], Khotanzad, A.[Alireza],
Fuzzy classifier design using genetic algorithms,
PR(40), No. 12, December 2007, pp. 3401-3414.
Elsevier DOI 0709
Fuzzy classifier; Genetic algorithms; Optimization of fuzzy parameters; Fuzzy rule extraction; Pattern classification BibRef

Mota, G.L.A.[Guilherme L.A.], Feitosa, R.Q.[Raul Q.], Coutinho, H.L.C.[Heitor L.C.], Liedtke, C.E.[Claus-Eberhard], Muller, S.[Sonke], Pakzad, K.[Kian], Meirelles, M.S.P.[Margareth S.P.],
Multitemporal fuzzy classification model based on class transition possibilities,
PandRS(62), No. 3, August 2007, pp. 186-200.
Elsevier DOI 0709
Remote sensing; Knowledge-base representation; Multitemporal interpretation; Fuzzy logic BibRef

Feitosa, R.Q.[Raul Q.], da Costa, G.A.O.P.[Gilson A.O.P.], Mota, G.L.A.[Guilherme L.A.], Pakzad, K.[Kian], Costa, M.C.O.[Maria C.O.],
Cascade multitemporal classification based on fuzzy Markov chains,
PandRS(64), No. 2, March 2009, pp. 159-170.
Elsevier DOI 0903
Cascade classifier; Multitemporal classification; Fuzzy classifier; Fuzzy Markov chain BibRef

Ding, Y.F.[Yun-Fei], Harrison, R.F.[Robert F.],
Relational visual cluster validity (RVCV),
PRL(28), No. 15, 1 November 2007, pp. 2071-2079.
Elsevier DOI 0711
Clustering; Cluster validity; Relational data; Non-Euclidean fuzzy c-means; Visual cluster validity BibRef

Cai, W.L.[Wei-Ling], Chen, S.C.[Song-Can], Zhang, D.Q.[Dao-Qiang],
Robust fuzzy relational classifier incorporating the soft class labels,
PRL(28), No. 16, December 2007, pp. 2250-2263.
Elsevier DOI 0711
Fuzzy c-means clustering (FCM); Fuzzy relations; Fuzzy relational classifier; Kernelized FCM (KFCM); Soft class label; Pattern classification BibRef

Masson, M.H.[Marie-Helene], Denoeux, T.,
ECM: An evidential version of the fuzzy c-means algorithm,
PR(41), No. 4, April 2008, pp. 1384-1397.
Elsevier DOI 0801
Clustering; Unsupervised learning; Dempster-Shafer theory; Evidence theory; Belief functions; Cluster validity; Robustness BibRef

Masson, M.H.[Marie-Helene], Denoeux, T.[Thierry],
RECM: Relational evidential c-means algorithm,
PRL(30), No. 11, 1 August 2009, pp. 1015-1026.
Elsevier DOI 0909
Clustering; Proximity data; Unsupervised learning; Dempster-Shafer theory; Belief functions BibRef

Mohamadi, H.[Hamid], Habibi, J.[Jafar], Abadeh, M.S.[Mohammad Saniee], Saadi, H.[Hamid],
Data mining with a simulated annealing based fuzzy classification system,
PR(41), No. 5, May 2008, pp. 1841-1850.
Elsevier DOI 0711
Simulated annealing; Data mining; Pattern classification; Fuzzy systems; Fuzzy rule extraction BibRef

Grira, N.[Nizar], Crucianu, M.[Michel], Boujemaa, N.[Nozha],
Active semi-supervised fuzzy clustering,
PR(41), No. 5, May 2008, pp. 1851-1861.
Elsevier DOI 0711
Semi-supervised clustering; Image database categorization; Pairwise constraints; Active learning BibRef

Laskaris, N.A.[Nikolaos A.], Zafeiriou, S.P.[Stefanos P.],
Beyond FCM: Graph-theoretic post-processing algorithms for learning and representing the data structure,
PR(41), No. 8, August 2008, pp. 2630-2644.
Elsevier DOI 0805
Fuzzy clustering; Manifold learning; Prototyping; Spectral-graph theory; Visual data mining BibRef

Zafeiriou, S.P.[Stefanos P.], Laskaris, N.A.[Nikolaos A.],
Nonnegative Embeddings and Projections for Dimensionality Reduction and Information Visualization,

Pedrycz, W.[Witold], Hirota, K.[Kaoru],
A consensus-driven fuzzy clustering,
PRL(29), No. 9, 1 July 2008, pp. 1333-1343.
Elsevier DOI 0711
Fuzzy clustering with consensus; Proximity matrix; Knowledge-based clustering; Local and global quality assessment of information granules
See also Fuzzy sets in pattern recognition: Methodology and methods. BibRef

Mitra, S.[Sushmita], Pedrycz, W.[Witold], Barman, B.[Bishal],
Shadowed c-means: Integrating fuzzy and rough clustering,
PR(43), No. 4, April 2010, pp. 1282-1291.
Elsevier DOI 1002
Shadowed sets; c-Means algorithm; Three-valued logic; Cluster validity index; Fuzzy sets; Rough sets BibRef

Miyamoto, S.[Sadaaki], Alanzado, A.C.[Arnold C.],
Fuzzy C-means And Mixture Distribution Models In The Presence Of Noise Clusters,
IJIG(2), No. 4, October 2002, pp. 573-586. 0210

Yang, M.S.[Miin-Shen], Tsai, H.S.[Hsu-Shen],
A Gaussian kernel-based fuzzy c-means algorithm with a spatial bias correction,
PRL(29), No. 12, 1 September 2008, pp. 1713-1725.
Elsevier DOI 0804
Fuzzy clustering; Fuzzy c-means (FCM); Gaussian kernel-based FCM; Spatial bias correction; Image segmentation; MRI data BibRef

Chatzis, S.P.[Sotirios P.], Varvarigou, T.A.[Theodora A.],
Robust fuzzy clustering using mixtures of Student's-t distributions,
PRL(29), No. 13, 1 October 2008, pp. 1901-1905.
Elsevier DOI 0804
Fuzzy clustering; Fuzzy c-means; Finite mixture models; Student's-t distributions BibRef

Fan, J.C.[Jian-Chao], Han, M.[Min], Wang, J.[Jun],
Single point iterative weighted fuzzy C-means clustering algorithm for remote sensing image segmentation,
PR(42), No. 11, November 2009, pp. 2527-2540.
Elsevier DOI 0907
Clustering; Attribute weights; Center initialization; Fuzzy C-means; Image segmentation BibRef

Wu, K.L.[Kuo-Lung], Yang, M.S.[Miin-Shen], Hsieh, J.N.[June-Nan],
Mountain c-regressions method,
PR(43), No. 1, January 2010, pp. 86-98.
Elsevier DOI 0909
Switching regressions; Fuzzy clustering; Fuzzy c-regressions; Mountain clustering; Mountain c-regressions BibRef

Falasconi, M., Gutierrez, A., Pardo, M., Sberveglieri, G., Marco, S.,
A stability based validity method for fuzzy clustering,
PR(43), No. 4, April 2010, pp. 1292-1305.
Elsevier DOI 1002
Fuzzy c-means; Cluster validity; Number of clusters; Cluster stability BibRef

Liu, J.[Jian],
Detecting the fuzzy clusters of complex networks,
PR(43), No. 4, April 2010, pp. 1334-1345.
Elsevier DOI 1002
Fuzzy clusters; Optimal prediction; k-Means; Fuzzy c-means; Steepest descent; Conjugate gradient; Projection BibRef

Fang, H.[Hua], Rizzo, M.L.[Maria L.], Wang, H.G.[Hong-Gang], Espy, K.A.[Kimberly Andrews], Wang, Z.Y.[Zhen-Yuan],
A new nonlinear classifier with a penalized signed fuzzy measure using effective genetic algorithm,
PR(43), No. 4, April 2010, pp. 1393-1401.
Elsevier DOI 1002
Choquet integral; Signed fuzzy measure; Classification; Optimization; Genetic algorithm BibRef

Yu, Z.D.[Zhi-Ding], Au, O.C.[Oscar C.], Zou, R.B.[Ruo-Bing], Yu, W.Y.[Wei-Yu], Tian, J.[Jing],
An adaptive unsupervised approach toward pixel clustering and color image segmentation,
PR(43), No. 5, May 2010, pp. 1889-1906.
Elsevier DOI 1003
Ant system; Clustering; Fuzzy C-means; Image segmentation BibRef

Yu, Z.D.[Zhi-Ding], Li, A.[Ang], Au, O.C.[Oscar C.], Xu, C.J.[Chun-Jing],
Bag of textons for image segmentation via soft clustering and convex shift,

Yu, Z.D.[Zhi-Ding], Au, O.C.[Oscar C.], Tang, K.[Ketan], Xu, C.J.[Chun-Jing],
Nonparametric density estimation on a graph: Learning framework, fast approximation and application in image segmentation,

Mei, J.P.[Jian-Ping], Chen, L.H.[Li-Hui],
Fuzzy clustering with weighted medoids for relational data,
PR(43), No. 5, May 2010, pp. 1964-1974.
Elsevier DOI 1003
Fuzzy clustering; (Dis)similarity-based; k-Medoids; Prototype weight BibRef

Egozi, A.[Amir], Keller, Y.[Yosi], Guterman, H.[Hugo],
Improving Shape Retrieval by Spectral Matching and Meta Similarity,
IP(19), No. 5, May 2010, pp. 1319-1327.

Egozi, A.[Amir], Keller, Y.[Yosi], Guterman, H.[Hugo],
A Probabilistic Approach to Spectral Graph Matching,
PAMI(35), No. 1, January 2013, pp. 18-27.

Krinidis, S., Chatzis, V.,
A Robust Fuzzy Local Information C-Means Clustering Algorithm,
IP(19), No. 5, May 2010, pp. 1328-1337.

See also Comments on A Robust Fuzzy Local Information C-Means Clustering Algorithm. BibRef

Son, C.S.[Chang Sik], Kim, Y.N.[Yoon-Nyun], Park, K.R.[Kyung-Ri], Park, H.J.[Hee-Joon],
Design of Hierarchical Fuzzy Classification System Based on Statistical Characteristics of Data,
IEICE(E93-D), No. 8, August 2010, pp. 2319-2323.
WWW Link. 1008

Maulik, U.[Ujjwal], Saha, I.[Indrajit],
Automatic Fuzzy Clustering Using Modified Differential Evolution for Image Classification,
GeoRS(48), No. 9, September 2010, pp. 3503-3510.

Saha, I.[Indrajit], Maulik, U.[Ujjwal], Bandyopadhyay, S.[Sanghamitra],
An Improved Multi-objective Technique for Fuzzy Clustering with Application to IRS Image Segmentation,
Springer DOI 0904

Pedrycz, W.[Witold], Bargiela, A.[Andrzej],
Fuzzy clustering with semantically distinct families of variables: Descriptive and predictive aspects,
PRL(31), No. 13, 1 October 2010, pp. 1952-1958.
Elsevier DOI 1003
Fuzzy clustering; Descriptive features; Functional features; Fuzzy C-means (FCM); Reconstruction criterion; Granulation-degranulation BibRef

Cheng, M.[Miao], Fang, B.[Bin], Wen, J.[Jing], Tang, Y.Y.[Yuan Yan],
Marginal discriminant projections: An adaptable margin discriminant approach to feature reduction and extraction,
PRL(31), No. 13, 1 October 2010, pp. 1965-1974.
Elsevier DOI 1003
Feature extraction; Dimensionality reduction; Maladjusted learning problem; Hierarchical fuzzy clustering; Curse of dimensionality BibRef

Tsai, D.M.[Du-Ming], Lin, C.C.[Chung-Chan],
Fuzzy C-means based clustering for linearly and nonlinearly separable data,
PR(44), No. 8, August 2011, pp. 1750-1760.
Elsevier DOI 1104
Clustering; Fuzzy C-means; Kernel fuzzy C-means; Distance metric BibRef

Ju, Z.J.[Zhao-Jie], Liu, H.H.[Hong-Hai],
Fuzzy Gaussian Mixture Models,
PR(45), No. 3, March 2012, pp. 1146-1158.
Elsevier DOI 1111
Fuzzy C-means; Gaussian Mixture Models; Fuzzy Gaussian Mixture Models; EM algorithm BibRef

Liu, Z.G.[Zhun-Ga], Dezert, J.[Jean], Mercier, G.[Grégoire], Pan, Q.[Quan],
Belief C-Means: An extension of Fuzzy C-Means algorithm in belief functions framework,
PRL(33), No. 3, 1 February 2012, pp. 291-300.
Elsevier DOI 1201
Unsupervised clustering; Data clustering; BCM; ECM; FCM; Belief functions BibRef

Graves, D.[Daniel], Noppen, J.[Joost], Pedrycz, W.[Witold],
Clustering with proximity knowledge and relational knowledge,
PR(45), No. 7, July 2012, pp. 2633-2644.
Elsevier DOI 1203
Relational clustering; Fuzzy clustering; Proximity; Knowledge representation; Software requirements BibRef

Mok, P.Y., Huang, H.Q., Kwok, Y.L., Au, J.S.,
A robust adaptive clustering analysis method for automatic identification of clusters,
PR(45), No. 8, August 2012, pp. 3017-3033.
Elsevier DOI 1204
Cluster analysis; Cluster validity; Fuzzy clustering; Fuzzy C-Means; Cluster ensembles BibRef

He, Y.Y.[Yan-Yan], Hussaini, M.Y.[M. Yousuff], Ma, J.W.[Jian-Wei], Shafei, B.[Behrang], Steidl, G.[Gabriele],
A new fuzzy c-means method with total variation regularization for segmentation of images with noisy and incomplete data,
PR(45), No. 9, September 2012, pp. 3463-3471.
Elsevier DOI 1206
Fuzzy c-means; Multi-class labeling; Sparsity-promoting method; Alternating direction method of multipliers; MRI segmentation; Noisy and incomplete data BibRef

Dagher, I.[Issam],
Complex fuzzy c-means algorithm,
AIR(38), No. 1, June 2012, pp. 25-39.
WWW Link. 1208

Mei, J.P.[Jian-Ping], Chen, L.H.[Li-Hui],
LinkFCM: Relation integrated fuzzy c-means,
PR(46), No. 1, January 2013, pp. 272-283.
Elsevier DOI 1209
Clustering; Fuzzy c-means; Pairwise relation; Semi-supervised; Document categorization BibRef

Huang, M.[Ming], Xia, Z.X.[Zhi-Xun], Wang, H.B.[Hong-Bo], Zeng, Q.H.[Qing-Hua], Wang, Q.[Qian],
The range of the value for the fuzzifier of the fuzzy c-means algorithm,
PRL(33), No. 16, 1 December 2012, pp. 2280-2284.
Elsevier DOI 1210
Fuzzy c-means algorithm; Fuzzifier; The range of the value; The behavior of membership function BibRef

Dagher, I.[Issam], Issa, S.[Saad],
Subband effect of the wavelet fuzzy C-means features in texture classification,
IVC(30), No. 11, November 2012, pp. 896-905.
Elsevier DOI 1211
Texture classification; Wavelet transform; FCM; Subbands; K-nearest neighbors BibRef

Kashan, A.H.[Ali Husseinzadeh], Rezaee, B.[Babak], Karimiyan, S.[Somayyeh],
An efficient approach for unsupervised fuzzy clustering based on grouping evolution strategies,
PR(46), No. 5, May 2013, pp. 1240-1254.
Elsevier DOI 1302
Clustering; Fuzzy; Grouping evolution strategy; Fuzzy c-means algorithm BibRef

Gong, M., Liang, Y., Shi, J., Ma, W., Ma, J.,
Fuzzy C-Means Clustering With Local Information and Kernel Metric for Image Segmentation,
IP(22), No. 2, February 2013, pp. 573-584.

Mújica-Vargas, D.[Dante], Gallegos-Funes, F.J.[Francisco J.], Rosales-Silva, A.J.[Alberto J.],
A fuzzy clustering algorithm with spatial robust estimation constraint for noisy color image segmentation,
PRL(34), No. 4, 1 March 2013, pp. 400-413.
Elsevier DOI 1302
Fuzzy C-Means; RM-L-estimator; L-estimator; Color images; SegmentationNoise BibRef

Vela-Rincón, V.V.[Virna V], Mújica-Vargas, D.[Dante], Lavalle, M.M.[Manuel Mejía], Salazar, A.M.[Andrea Magadán],
Spatial a: Trimmed Fuzzy C-Means Algorithm to Image Segmentation,
Springer DOI 2007

Mújica-Vargas, D.[Dante], Gallegos-Funes, F.J.[Francisco J.], Rosales-Silva, A.J.[Alberto J.], de Jesús Rubio, J.[José],
Robust c-prototypes algorithms for color image segmentation,
JIVP(2013), No. 1, 2013, pp. 63.
DOI Link 1312

Celik, T., Lee, H.K.,
Comments on 'A Robust Fuzzy Local Information C-Means Clustering Algorithm',
IP(22), No. 3, March 2013, pp. 1258-1261.

See also Robust Fuzzy Local Information C-Means Clustering Algorithm, A. BibRef

Xu, C.[Chao], Zhang, P.L.[Pei-Lin], Li, B.[Bing], Wu, D.H.[Ding-Hai], Fan, H.B.[Hong-Bo],
Vague C-means clustering algorithm,
PRL(34), No. 5, 1 April 2013, pp. 505-510.
Elsevier DOI 1303
Fuzzy clustering; Vague set (VS); Quantum-behaved particle swarm optimization (QPSO) BibRef

Lai, J.Z.C.[Jim Z.C.], Juan, E.Y.T.[Eric Y.T.], Lai, F.J.C.[Franklin J.C.],
Rough clustering using generalized fuzzy clustering algorithm,
PR(46), No. 9, September 2013, pp. 2538-2547.
Elsevier DOI 1305
Rough k-means clustering; Nearest-neighbor search; Knowledge discovery; Soft computing BibRef

Verbiest, N.[Nele], Cornelis, C.[Chris], Herrera, F.[Francisco],
FRPS: A Fuzzy Rough Prototype Selection method,
PR(46), No. 10, October 2013, pp. 2770-2782.
Elsevier DOI 1306
Classification; Fuzzy rough sets; Instance selection; k NN; Prototype Selection BibRef

Meher, S.K.[Saroj K.],
Explicit rough-fuzzy pattern classification model,
PRL(36), No. 1, 2014, pp. 54-61.
Elsevier DOI 1312
Pattern recognition BibRef

Lin, P.L.[Phen-Lan], Huang, P.W.[Po-Whei], Kuo, C.H., Lai, Y.H.,
A size-insensitive integrity-based fuzzy c-means method for data clustering,
PR(47), No. 5, 2014, pp. 2042-2056.
Elsevier DOI 1402
Fuzzy c-means BibRef

Zhao, Z.X.[Zai-Xin], Cheng, L.Z.[Li-Zhi], Cheng, G.Q.[Guang-Quan],
Neighbourhood weighted fuzzy c-means clustering algorithm for image segmentation,
IET-IPR(8), No. 3, March 2014, pp. 150-161.
DOI Link 1404
fuzzy set theory BibRef

ben N'Cir, C.E.[Chiheb-Eddine], Cleuziou, G.[Guillaume], Essoussi, N.[Nadia],
Generalization of c-means for identifying non-disjoint clusters with overlap regulation,
PRL(45), No. 1, 2014, pp. 92-98.
Elsevier DOI 1407
Overlapping clustering BibRef

Liu, J.[Jin], Pham, T.D.[Tuan D.],
A spatially constrained fuzzy hyper-prototype clustering algorithm,
PR(45), No. 4, 2012, pp. 1759-1771.
Elsevier DOI 1410
Fuzzy c-means BibRef

Khalilia, M.A.[Mohammed A.], Bezdek, J.[James], Popescu, M.[Mihail], Keller, J.M.[James M.],
Improvements to the relational fuzzy c-means clustering algorithm,
PR(47), No. 12, 2014, pp. 3920-3930.
Elsevier DOI 1410
Fuzzy clustering BibRef

Jiang, Y., Chung, F., Wang, S., Deng, Z., Wang, J., Qian, P.,
Collaborative Fuzzy Clustering From Multiple Weighted Views,
Cyber(45), No. 4, April 2015, pp. 688-701.
Algorithm design and analysis BibRef

Suleman, A.[Abdul],
A new perspective of modified partition coefficient,
PRL(56), No. 1, 2015, pp. 1-6.
Elsevier DOI 1503
Fuzzy clustering BibRef

Guo, Y.H.[Yan-Hui], Sengur, A.[Abdulkadir],
NCM: Neutrosophic c-means clustering algorithm,
PR(48), No. 8, 2015, pp. 2710-2724.
Elsevier DOI 1505
Data clustering BibRef

Chen, K.[Kun], Li, Y.[Yuehua], Xu, X.J.[Xing-Jian],
Radar HRRP Target Recognition Based on the Improved Kernel Distance Fuzzy C-Means Clustering Method,
IEICE(E98-D), No. 9, September 2015, pp. 1683-1690.
WWW Link. 1509

Guo, F.F., Wang, X.X., Shen, J.,
Adaptive fuzzy c-means algorithm based on local noise detecting for image segmentation,
IET-IPR(10), No. 4, 2016, pp. 272-279.
DOI Link 1604
adaptive signal processing BibRef

d'Urso, P.[Pierpaolo], Leski, J.M.[Jacek M.],
Fuzzy c-ordered medoids clustering for interval-valued data,
PR(58), No. 1, 2016, pp. 49-67.
Elsevier DOI 1606
Interval-valued data BibRef

Saha, A.[Arkajyoti], Das, S.[Swagatam],
Geometric divergence based fuzzy clustering with strong resilience to noise features,
PRL(79), No. 1, 2016, pp. 60-67.
Elsevier DOI 1608
Fuzzy Clustering BibRef

Hofmann, P.[Peter],
Defuzzification Strategies for Fuzzy Classifications of Remote Sensing Data,
RS(8), No. 6, 2016, pp. 467.
DOI Link 1608

Zhou, K.[Kuang], Martin, A.[Arnaud], Pan, Q.[Quan], Liu, Z.G.[Zhun-Ga],
ECMdd: Evidential c-medoids clustering with multiple prototypes,
PR(60), No. 1, 2016, pp. 239-257.
Elsevier DOI 1705
Credal partitions BibRef

Memon, K.H.[Kashif Hussain], Lee, D.H.[Dong-Ho],
Generalised fuzzy c-means clustering algorithm with local information,
IET-IPR(11), No. 1, January 2017, pp. 1-12.
DOI Link 1703

Jiang, Z.H.[Zhao-Hui], Li, T.T.[Ting-Ting], Min, W.F.[Wen-Fang], Qi, Z.[Zhao], Rao, Y.[Yuan],
Fuzzy c-means clustering based on weights and gene expression programming,
PRL(90), No. 1, 2017, pp. 1-7.
Elsevier DOI 1704
Data clustering BibRef

Yang, M.S.[Miin-Shen], Nataliani, Y.[Yessica],
Robust-learning fuzzy c-means clustering algorithm with unknown number of clusters,
PR(71), No. 1, 2017, pp. 45-59.
Elsevier DOI 1707
Fuzzy, clustering BibRef

Zhang, H., Wang, Q., Shi, W., Hao, M.,
A Novel Adaptive Fuzzy Local Information C-Means Clustering Algorithm for Remotely Sensed Imagery Classification,
GeoRS(55), No. 9, September 2017, pp. 5057-5068.
fuzzy set theory, geophysical image processing, geophysical techniques, image classification, ADFLICM approach, ADFLICM images, conventional fuzzy c-means algorithm, local spatial level information, remotely sensed imagery, spatial information BibRef

Guo, J.[Jifa], Huo, H.Y.[Hong-Yuan],
An Enhanced IT2FCM* Algorithm Integrating Spectral Indices and Spatial Information for Multi-Spectral Remote Sensing Image Clustering,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
Interval type-2 fuzzy c-means. BibRef

Biswas, N.[Nimagna], Chakraborty, S.[Saurajit], Mullick, S.S.[Sankha Subhra], Das, S.[Swagatam],
A parameter independent fuzzy weighted k-Nearest neighbor classifier,
PRL(101), No. 1, 2018, pp. 80-87.
Elsevier DOI 1801
Fuzzy k-Nearest neighbor BibRef

Bonis, T.[Thomas], Oudot, S.[Steve],
A fuzzy clustering algorithm for the mode-seeking framework,
PRL(102), 2018, pp. 37-43.
Elsevier DOI 1802
Fuzzy clustering, Mode seeking, Random geometric graph, Random walk BibRef

Chetih, N.[Nabil], Messali, Z.[Zoubeida], Serir, A.[Amina], Ramou, N.[Naim],
Robust fuzzy c-means clustering algorithm using non-parametric Bayesian estimation in wavelet transform domain for noisy MR brain image segmentation,
IET-IPR(12), No. 5, May 2018, pp. 652-660.
DOI Link 1804

Hu, X.C.[Xing-Chen], Pedrycz, W.[Witold], Wang, X.M.[Xian-Min],
Fuzzy classifiers with information granules in feature space and logic-based computing,
PR(80), 2018, pp. 156-167.
Elsevier DOI 1805
Fuzzy classifiers, Performance analysis, Logic processing, Receiver operating characteristics, Triangular norms, Particle swarm optimizer (PSO) BibRef

Ngo, L.T.[Long Thanh], Dang, T.H.[Trong Hop], Pedrycz, W.[Witold],
Towards interval-valued fuzzy set-based collaborative fuzzy clustering algorithms,
PR(81), 2018, pp. 404-416.
Elsevier DOI 1806
Fuzzy C-Means (FCM), Collaborative fuzzy clustering, Interval-valued fuzzy clustering, Interval type-2 fuzzy sets, Clustering validity index BibRef

Zhou, X.[Xiangbing], Miao, F.[Fang], Ma, H.J.[Hong-Jiang], Zhang, H.[Hua], Gong, H.[Huaming],
A Trajectory Regression Clustering Technique Combining a Novel Fuzzy C-Means Clustering Algorithm with the Least Squares Method,
IJGI(7), No. 5, 2018, pp. xx-yy.
DOI Link 1806

Abdelghaffar, N.M.[Nashwa M.], Lotfy, H.M.S.[Hewayda M. S.], Khamis, S.M.[Soheir M.],
A multi-agent-based approach for fuzzy clustering of large image data,
RealTimeIP(15), No. 2, August 2018, pp. 235-247.
Springer DOI 1808

Yang, X.H.[Xiao-Hong], Xie, Z.[Zhong], Ling, F.[Feng], Li, X.D.[Xiao-Dong], Zhang, Y.H.[Yi-Hang], Zhong, M.[Ming],
Spatio-Temporal Super-Resolution Land Cover Mapping Based on Fuzzy C-Means Clustering,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809

Lu, Z.Y.[Zhen-Yu], Qiu, Y.[Yunan], Zhan, T.M.[Tian-Ming],
Neutrosophic C-means clustering with local information and noise distance-based kernel metric image segmentation,
JVCIR(58), 2019, pp. 269-276.
Elsevier DOI 1901
Image segmentation, Noise clustering, Fuzzy clustering, Nutrosophic clustering BibRef

Trabelsi, M.[Mohamed], Frigui, H.[Hichem],
Robust fuzzy clustering for multiple instance regression,
PR(90), 2019, pp. 424-435.
Elsevier DOI 1903
Multiple instance regression, Fuzzy clustering, Possibilistic clustering, Multiple model regression BibRef

Chen, X.J.[Xiang-Jian], Li, D.[Di], Wang, X.[Xun], Yang, X.B.[Xi-Bei], Li, H.M.[Hong-Mei],
Rough intuitionistic type-2 fuzzy c-means clustering algorithm for MR image segmentation,
IET-IPR(13), No. 4, March 2019, pp. 607-614.
DOI Link 1903

Verma, H.[Hanuman], Gupta, A.[Akshansh], Kumar, D.[Dhirendra],
A modified intuitionistic fuzzy c-means algorithm incorporating hesitation degree,
PRL(122), 2019, pp. 45-52.
Elsevier DOI 1904
Intuitionistic fuzzy set, Fuzzy c-means, Intuitionistic fuzzy c-means, Clustering BibRef

Zhang, L.L.[Ling-Ling], Luo, M.[Minnan], Liu, J.[Jun], Li, Z.H.[Zhi-Hui], Zheng, Q.H.[Qing-Hua],
Diverse fuzzy c-means for image clustering,
PRL(130), 2020, pp. 275-283.
Elsevier DOI 2002
Image clustering, Diversity regularization, Fuzzy -means, Cluster one-sidedness BibRef

Kumar, S.[Sandeep], Suresh, L.,
Fruit Fly-Based Artificial Neural Network Classifier with Kernel-Based Fuzzy c-Means Clustering for Satellite Image Classification,
IJIG(20), No. 2, April 2020, pp. 2050016.
DOI Link 2005

Wang, C., Pedrycz, W., Yang, J., Zhou, M., Li, Z.,
Wavelet Frame-Based Fuzzy C-Means Clustering for Segmenting Images on Graphs,
Cyber(50), No. 9, September 2020, pp. 3938-3949.
Image segmentation, Wavelet transforms, Clustering algorithms, Image edge detection, Computational modeling, Kernel, tight wavelet frames BibRef

Kulkarni, O.[Omkaresh], Jena, S.[Sudarson], Sankar, V.R.[V. Ravi],
MapReduce framework based big data clustering using fractional integrated sparse fuzzy C means algorithm,
IET-IPR(14), No. 12, October 2020, pp. 2719-2727.
DOI Link 2010

Kumbure, M.M.[Mahinda Mailagaha], Luukka, P.[Pasi], Collan, M.[Mikael],
A new fuzzy k-nearest neighbor classifier based on the Bonferroni mean,
PRL(140), 2020, pp. 172-178.
Elsevier DOI 2012
Bonferroni mean, Classification, Fuzzy -nearest neighbor, Performance measures, Local means BibRef

Bose, A.[Ankita], Mali, K.[Kalyani],
Type-reduced vague possibilistic fuzzy clustering for medical images,
PR(112), 2021, pp. 107784.
Elsevier DOI 2102
Fuzzy membership, Typicality, Vague set, Type-reduction, Medical images BibRef

Zhou, J.[Jie], Pedrycz, W.[Witold], Yue, X.D.[Xiao-Dong], Gao, C.[Can], Lai, Z.H.[Zhi-Hui], Wan, J.[Jun],
Projected fuzzy C-means clustering with locality preservation,
PR(113), 2021, pp. 107748.
Elsevier DOI 2103
Fuzzy C-means, Locality preserving projections, Clustering, Projection-based spatial transformation BibRef

Wu, C.[Chong], Zheng, J.B.[Jiang-Bin], Feng, Z.A.[Zhen-An], Zhang, H.W.[Hou-Wang], Zhang, L.[Le], Cao, J.W.[Jia-Wang], Yan, H.[Hong],
Fuzzy SLIC: Fuzzy Simple Linear Iterative Clustering,
CirSysVideo(31), No. 6, June 2021, pp. 2114-2124.
Clustering algorithms, Robustness, Noise measurement, Scalp, Heuristic algorithms, Visualization, Iterative methods, superpixel segmentation BibRef

Yang, M.S.[Miin-Shen], Sinaga, K.P.[Kristina P.],
Collaborative feature-weighted multi-view fuzzy c-means clustering,
PR(119), 2021, pp. 108064.
Elsevier DOI 2106
Clustering, Fuzzy c-means (FCM), Multi-view FCM (MVFCM), Collaborative learning, Feature weights, Feature reduction BibRef

Yang, Z.Z.[Zhen-Zhen], Xu, P.F.[Peng-Fei], Yang, Y.P.[Yong-Peng], Kang, B.[Bin],
Noise robust intuitionistic fuzzy c-means clustering algorithm incorporating local information,
IET-IPR(15), No. 3, 2021, pp. 805-817.
DOI Link 2106

Madhu, A.[Anjali], Kumar, A.[Anil], Jia, P.[Peng],
Exploring Fuzzy Local Spatial Information Algorithms for Remote Sensing Image Classification,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110

Li, H.J.[Hong-Jun], Zhou, Z.[Ze], Li, C.[Chaobo], Suen, C.Y.[Ching Y.],
A near effective and efficient model in recognition,
PR(122), 2022, pp. 108173.
Elsevier DOI 2112
Pattern recognition, Hierarchical structure, Fuzzy system, Cycle mechanism BibRef

Kazerouni, I.A.[Iman Abaspur], Mahdipour, H.[Hadi], Dooly, G.[Gerard], Toal, D.[Daniel],
Vector Fuzzy c-Spherical Shells (VFCSS) over Non-Crisp Numbers for Satellite Imaging,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112

Chen, Y.X.[Yu-Xue], Zhou, S.S.[Shui-Sheng], Zhang, X.M.[Xi-Min], Li, D.[Dong], Fu, C.[Cui],
Improved fuzzy c-means clustering by varying the fuzziness parameter,
PRL(157), 2022, pp. 60-66.
Elsevier DOI 2205
Fuzzy c-means, Fuzziness parameter, Careful tuning, Deterministic annealing BibRef

Ji, X.R.[Xin-Ran], Huang, L.[Liang], Tang, B.H.[Bo-Hui], Chen, G.[Guokun], Cheng, F.F.[Fei-Fei],
A Superpixel Spatial Intuitionistic Fuzzy C-Means Clustering Algorithm for Unsupervised Classification of High Spatial Resolution Remote Sensing Images,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208

Zhang, Z.[Zhou], Wang, D.[Degang], Sun, X.[Xu], Zhuang, L.[Lina], Liu, R.[Rong], Ni, L.[Li],
Spatial Sampling and Grouping Information Entropy Strategy Based on Kernel Fuzzy C-Means Clustering Method for Hyperspectral Band Selection,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210

Liu, H.[Han], Wu, C.[Chengmao], Li, C.X.[Chang-Xing], Zuo, Y.[Yanqun],
Fast robust fuzzy clustering based on bipartite graph for hyper-spectral image classification,
IET-IPR(16), No. 13, 2022, pp. 3634-3647.
DOI Link 2210

Yang, M.S.[Miin-Shen], Benjamin, J.B.M.[Josephine B.M.],
Sparse possibilistic c-means clustering with Lasso,
PR(138), 2023, pp. 109348.
Elsevier DOI 2303
Clustering, Possibilistic c-means (PCM), Feature weights, Sparsity, Lasso, Spare PCM (S-PCM) BibRef

Wu, J.X.[Jia-Xin], Wang, X.P.[Xiao-Peng], Wei, T.[Tongyi], Fang, C.[Chao],
Full-parameter adaptive fuzzy clustering for noise image segmentation based on non-local and local spatial information,
CVIU(235), 2023, pp. 103765.
Elsevier DOI 2310
Fuzzy C-Means clustering, Local and non-local spatial information, Noise image segmentation BibRef

Tang, Y.M.[Yi-Ming], Pan, Z.[Zhifu], Hu, X.H.[Xiang-Hui], Pedrycz, W.[Witold], Chen, R.[Renhao],
Knowledge-Induced Multiple Kernel Fuzzy Clustering,
PAMI(45), No. 12, December 2023, pp. 14838-14855.

Wang, J.Y.[Jing-Yu], Wang, Y.[Yidi], Nie, F.P.[Fei-Ping], Li, X.L.[Xue-Long],
Discriminative projection fuzzy K-Means with adaptive neighbors,
PRL(176), 2023, pp. 21-27.
Elsevier DOI 2312
Unsupervised clustering, Fuzzy K-means, Projection subspace, Discriminative fuzzy clustering, Adaptive neighbors BibRef

Zhang, C.Y.[Chu-Yun], Xie, W.X.[Wei-Xin], Li, Y.[Yanshan], Liu, Z.X.[Zong-Xiang],
Multi-Source T-S Target Recognition via an Intuitionistic Fuzzy Method,
RS(15), No. 24, 2023, pp. 5773.
DOI Link 2401
Takagi-Sugeno fuzzy rules. BibRef

Leroy, C.[Clement], Anquetil, E.[Eric], Girard, N.[Nathalie],
Drift anticipation with forgetting to improve evolving fuzzy system,
Learning systems, Upper bound, Sensitivity, Windup, Data models, Stability analysis, Robustness, Evolving Fuzzy System EFS, Anticipation BibRef

Motaki, S.E., Yahyaouy, A., Gualous, H., Sabor, J.,
A new weighted fuzzy c-means based on the collective behaviour of starling birds,
fuzzy set theory, pattern clustering, elementary movements, starling bird, clustering validation indices, Clustering validation BibRef

Chakraborti, T., McCane, B., Mills, S., Pal, U.,
Fine-grained Collaborative K-Means Clustering,
Collaboration, Clustering algorithms, Birds, Task analysis, Clustering methods, Feature extraction, Benchmark testing, Fine-grained Recognition BibRef

El Motaki, S., Ali, Y., Gualous, H., Sabor, J.,
Possibilistic fuzzy C-means clustering under observer-biased framework,
fuzzy set theory, learning (artificial intelligence), pattern clustering, Possibilistic Fuzzy, observer-biased clustering BibRef

Lazo-Cortés, M.S.[Manuel S.], Martínez-Trinidad, J.F.[José Francisco], Carrasco-Ochoa, J.A.[Jesús Ariel],
A Glance to the Goldman's Testors from the Point of View of Rough Set Theory,
Springer DOI 1608

Dyrmann, M.[Mads],
Fuzzy c-means based plant segmentation with distance dependent threshold,
DOI Link 1601

Ben Said, A., Hadjidj, R., Foufou, S.,
Gravitational weighted fuzzy c-means with application on multispectral image segmentation,
fuzzy set theory BibRef

Ben, S.[Shenglan], Jin, Z.[Zhong], Yang, J.Y.[Jing-Yu],
Automatic fuzzy clustering based on mistake analysis,
WWW Link. 1302

Gupta, A.[Ashish], Bowden, R.[Richard],
Fuzzy encoding for image classification using Gustafson-Kessel algorithm,

Grandchamp, E.[Enguerran], Régis, S.[Sébastien], Rousteau, A.[Alain],
Vector Transition Classes Generation from Fuzzy Overlapping Classes,
Springer DOI 1209

Dwivedi, R., Kumar, A., Ghosh, S.K., Roy, P.S.,
Optimisation of Fuzzy Based Soft Classifiers for Remote Sensing Data,
DOI Link 1209

Park, D.C.[Dong-Chul],
Satellite Image Classification Using a Divergence-Based Fuzzy c-Means Algorithm,
Springer DOI 1208

See also Classification of Audio Signals Using Fuzzy C-Means with Divergence-Based Kernel. BibRef

Kaur, P.[Prabhjot], Soni, A.K., Gosain, A.[Anjana],
Robust Intuitionistic Fuzzy C-means clustering for linearly and nonlinearly separable data,

Rojas, D.[Dario], Zambrano, C.[Carolina], Varas, M.[Marcela], Urrutia, A.[Angelica],
A Multi-level Thresholding-Based Method to Learn Fuzzy Membership Functions from Data Warehouse,
Springer DOI 1111

Ayech, M.W.[Mohamed Walid], El Kalti, K.[Karim], El Ayeb, B.[Bechir],
Image Segmentation Based on Adaptive Fuzzy-C-Means Clustering,

Dehzangi, O.[Omid], Ma, B.[Bin], Chng, E.S.[Eng Siong], Li, H.Z.[Hai-Zhou],
Framewise Phone Classification Using Weighted Fuzzy Classification Rules,

Manikonda, L., Mangalampalli, A., Pudi, V.,
UACI: Uncertain associative classifier for object class identification in images,

Mangalampalli, A.[Ashish], Chaoji, V.[Vineet], Sanyal, S.[Subhajit],
I-FAC: Efficient Fuzzy Associative Classifier for Object Classes in Images,

Saad, M.F.[Mohamed Fadhel], Alimi, A.M.[Adel M.],
Improved Modified Suppressed Fuzzy C-Means,

Peng, D.Q.[Dai-Qiang], Ling, Y.[Yun], Wang, Y.[Yang],
Improving fuzzy c-means clustering based on local membership variation,

Janiš, V.[Vladimír], Rencova, M.[Magdalena], Šešelja, B.[Branimir], Tepavcevic, A.[Andreja],
Construction of Fuzzy Relation by Closure Systems,
Springer DOI 0912

Fabijanska, A.[Anna],
A Fuzzy Segmentation Method for Images of Heat-Emitting Objects,
Springer DOI 0911

Jiang, M.[Ming], Wang, Z.L.[Zhe-Long],
A Method for Stress Detection Based on FCM Algorithm,
FCM: fuzzy c-means BibRef

Guliato, D.[Denise], de Sousa Santos, J.C.[Jean Carlo],
Granular Computing and Rough Sets to Generate Fuzzy Rules,
Springer DOI 0907

Ahmed, E.[Eman], El Gayar, N.[Neamat], Atiya, A.F.[Amir F.], El Azab, I.A.[Iman A.],
Fuzzy Gaussian Process Classification Model,
Springer DOI 0907

Yu, Z.D.[Zhi-Ding], Zou, R.B.[Ruo-Bing], Yu, S.[Simin],
A modified fuzzy c-means algorithm with adaptive spatial information for color image segmentation,

Zhang, M.R.[Ming-Rui], Therneau, T.[Terry], McKenzie, M.A.[Michael A.], Li, P.[Peter], Yang, P.[Ping],
A fuzzy c-means algorithm using a correlation metrics and gene ontology,

Iakovidis, D.K.[Dimitris K.], Pelekis, N.[Nikos], Kotsifakos, E.[Evangelos], Kopanakis, I.[Ioannis],
Intuitionistic Fuzzy Clustering with Applications in Computer Vision,
Springer DOI 0810

Kannappady, S.[Srinidhi], Mudur, S.P.[Sudhir P.], Shiri, N.[Nematollaah],
Clickstream Visualization Based on Usage Patterns,
Springer DOI 0612
Fuzzy clustering, view as point cloud. BibRef

Wu, X.H.[Xiao-Hong], Zhou, J.J.[Jian-Jiang],
An Improved Possibilistic C-Means Algorithm Based on Kernel Methods,
Springer DOI 0608

Bao, Z.Q.[Zhi-Qiang], Han, B.[Bing], Wu, S.J.[Shun-Jun],
A General Weighted Fuzzy Clustering Algorithm,
ICIAR06(II: 102-109).
Springer DOI 0610

Bhattacharya, P.[Prabir], Rahman, M.[Mahmudur], Desai, B.C.[Bipin C.],
Image Representation and Retrieval Using Support Vector Machine and Fuzzy C-means Clustering Based Semantical Spaces,
ICPR06(I: 929-935).
And: ICPR06(II: 1162-1168).

Petrosino, A., Verde, M.,
P-AFLC: a parallel scalable fuzzy clustering algorithm,
ICPR04(I: 809-812).

Manley-Cooke, P., Razaz, M.,
A modified fuzzy inference system for pattern classification,
ICPR04(I: 256-259).

Muhammed, H.H.,
Unsupervised fuzzy clustering and image segmentation using weighted neural networks,

Abe, S.,
Generalization Improvement of a Fuzzy Classifier with Pyramidal Membership Functions,
ICPR00(Vol II: 211-214).

Lorette, A.[Anne], Descombes, X.[Xavier], Zerubia, J.B.[Josiane B.],
Fully Unsupervised Fuzzy Clustering with Entropy Criterion,
ICPR00(Vol III: 986-989).
IEEE DOI BibRef 0001 ICPR00(Vol III: 998-1001).

Gao, Q.G.[Qi-Gang], Qing, D.[Dan], Lu, S.W.[Si-Wei],
Fuzzy Classification of Generic Edge Features,
ICPR00(Vol III: 668-671).

Han, J.H.[Joon H.], Kim, Y.K.[Yoon K.],
A Fuzzy K-NN Algorithm using Weights from the Variance of Membership Values,
CVPR99(II: 394-399).
IEEE DOI BibRef 9900

Doroodchi, M.[Mahmood], Reza, A.M.,
Fuzzy Cluster Filter,
ICIP96(II: 939-942).
IEEE DOI BibRef 9600

Jozwik, A., Chmielewski, L., Cudny, W., Sklodowski, M.,
A 1-NN Preclassifier for Fuzzy K-NN Rule,
ICPR96(IV: 234-238).
(Polish Academy of Sciences, PL) BibRef

Qing, Y.X.[Ye Xiu], Hua, H.Z.[Huang Zhen], Qiang, X.[Xiao],
Histogram based fuzzy C-mean algorithm for image segmentation,

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Fuzzy Clustering, Cluster Validity Tests .

Last update:Apr 10, 2024 at 09:54:40