{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T11:28:48Z","timestamp":1762342128214,"version":"3.37.3"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2023,8,26]],"date-time":"2023-08-26T00:00:00Z","timestamp":1693008000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,8,26]],"date-time":"2023-08-26T00:00:00Z","timestamp":1693008000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62071379"],"award-info":[{"award-number":["62071379"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Memetic Comp."],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1007\/s12293-023-00396-x","type":"journal-article","created":{"date-parts":[[2023,8,26]],"date-time":"2023-08-26T07:01:58Z","timestamp":1693033318000},"page":"451-468","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Multiple population-based multi-objective evolutionary semi-supervised multi-kernel region fuzzy clustering image segmentation"],"prefix":"10.1007","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0323-9573","authenticated-orcid":false,"given":"Feng","family":"Zhao","sequence":"first","affiliation":[]},{"given":"Mimi","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8774-8625","authenticated-orcid":false,"given":"Hanqiang","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,8,26]]},"reference":[{"key":"396_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.neucom.2018.01.091","volume":"292","author":"F Garcia-Lamont","year":"2018","unstructured":"Garcia-Lamont F, Cervantes J, Lopez A, Rodriguez L (2018) Segmentation of images by color features: a survey. Neurocomputing 292:1\u201327","journal-title":"Neurocomputing"},{"key":"396_CR2","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1016\/j.neucom.2017.02.040","volume":"240","author":"L He","year":"2017","unstructured":"He L, Huang S (2017) Modified firefly algorithm based multilevel thresholding for color image segmentation. Neurocomputing 240:152\u2013174","journal-title":"Neurocomputing"},{"key":"396_CR3","doi-asserted-by":"crossref","unstructured":"Xue J, He X, Yang X, et al. (2017) Multi-threshold image segmentation method based on flower pollination algorithm. In: International conference on bio-inspired computing: theories & applications. Springer, Singapore, pp. 39\u201351","DOI":"10.1007\/978-981-10-7179-9_4"},{"issue":"2","key":"396_CR4","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1109\/TFUZZ.2018.2852289","volume":"27","author":"F Zhao","year":"2019","unstructured":"Zhao F, Fan JL, Liu HQ et al (2019) Noise robust multi-objective evolutionary clustering image segmentation motivated by intuitionistic fuzzy information. IEEE Trans Fuzzy Syst 27(2):387\u2013401","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"396_CR5","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1016\/j.ins.2013.10.002","volume":"262","author":"A Ortiz","year":"2014","unstructured":"Ortiz A, Gorriz JM, Ramirez J, Salasgonzalez D (2014) Improving MR brain image segmentation using self-organising maps and entropy-gradient clustering. Inf Sci 262:117\u2013136","journal-title":"Inf Sci"},{"issue":"4","key":"396_CR6","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1109\/TMI.2004.824224","volume":"23","author":"V Grau","year":"2004","unstructured":"Grau V, Mewes AU, Alcaniz M et al (2004) Improved watershed transform for medical image segmentation using prior information. IEEE Trans Med Imaging 23(4):447\u2013458","journal-title":"IEEE Trans Med Imaging"},{"issue":"2","key":"396_CR7","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1109\/91.493905","volume":"4","author":"A Bensaid","year":"1996","unstructured":"Bensaid A, Hall LO, Bezdek JC et al (1996) Validity-guided (re)clustering with applications to image segmentation. IEEE Trans Fuzzy Syst 4(2):112\u2013123","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"396_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-0450-1","volume-title":"Pattern recognition with fuzzy objective function algorithms","author":"JC Bezdek","year":"1981","unstructured":"Bezdek JC (1981) Pattern recognition with fuzzy objective function algorithms. Plenum Press, New York"},{"key":"396_CR9","doi-asserted-by":"crossref","unstructured":"Hathaway RJ, Huband JM, Bezdek JC, et al. (2005) Kernelized non-Euclidean relational fuzzy c-means algorithm. In: Proceeding of the 14th IEEE international conference on fuzzy systems, Reno, USA, pp. 414\u2013419","DOI":"10.1109\/FUZZY.2005.1452429"},{"key":"396_CR10","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1016\/j.asoc.2015.04.058","volume":"34","author":"Y Wu","year":"2015","unstructured":"Wu Y, Ma W, Gong M et al (2015) Novel fuzzy active contour model with kernel metric for image segmentation. Appl Soft Comput 34:301\u2013311","journal-title":"Appl Soft Comput"},{"issue":"5","key":"396_CR11","doi-asserted-by":"publisher","first-page":"1263","DOI":"10.1109\/TSMCB.2011.2124455","volume":"41","author":"L Chen","year":"2011","unstructured":"Chen L, Chen CL, Lu M et al (2011) A multiple-kernel fuzzy c-means algorithm for image segmentation. IEEE Trans Syst Man Cybern B Cybern 41(5):1263\u20131274","journal-title":"IEEE Trans Syst Man Cybern B Cybern"},{"issue":"01","key":"396_CR12","doi-asserted-by":"publisher","first-page":"1954003","DOI":"10.1142\/S021800141954003X","volume":"33","author":"G Hu","year":"2019","unstructured":"Hu G, Du Z (2019) Adaptive kernel-based fuzzy c-means clustering with spatial constraints for image segmentation. Int J Pattern Recognit Artif Intell 33(01):1954003","journal-title":"Int J Pattern Recognit Artif Intell"},{"issue":"4","key":"396_CR13","doi-asserted-by":"publisher","first-page":"522","DOI":"10.1016\/j.fss.2009.10.021","volume":"161","author":"D Graves","year":"2010","unstructured":"Graves D, Pedrycz W (2010) Kernel-based fuzzy clustering and fuzzy clustering: a comparative experimental study. Fuzzy Sets Syst 161(4):522\u2013543","journal-title":"Fuzzy Sets Syst"},{"key":"396_CR14","doi-asserted-by":"crossref","unstructured":"Yu CY, Li Y, Liu AL, et al. (2011) A novel modified kernel fuzzy c-means clustering algorithm on image segmentation. In: Processing of 14th IEEE international conference on computational science and engineering, Dalian, China, pp. 621\u2013626","DOI":"10.1109\/CSE.2011.109"},{"key":"396_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.108153","volume":"114","author":"L Wang","year":"2022","unstructured":"Wang L (2022) Imbalanced credit risk prediction based on SMOTE and multi-kernel FCM improved by particle swarm optimization. Appl Soft Comput 114:108153","journal-title":"Appl Soft Comput"},{"key":"396_CR16","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.neucom.2021.02.062","volume":"443","author":"DY Tan","year":"2021","unstructured":"Tan DY, Peng X, Wang Q et al (2021) Automatic determining optimal parameters in multi-kernel collaborative fuzzy clustering based on dimension constraint. Neurocomputing 443:58\u201374","journal-title":"Neurocomputing"},{"key":"396_CR17","doi-asserted-by":"crossref","unstructured":"Yasunori E, Yukihiro H, Makito Y, et al. (2009) On semi-supervised fuzzy c-means clustering. In: IEEE international conference on fuzzy systems, Jeju Island, South Korea, pp. 1119\u20131124","DOI":"10.1109\/FUZZY.2009.5277177"},{"key":"396_CR18","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1016\/j.engappai.2017.01.003","volume":"59","author":"LH Son","year":"2017","unstructured":"Son LH, Tuan TM (2017) Dental segmentation from X-ray images using semi-supervised fuzzy clustering with spatial constraints. Eng Appl Artif Intell 59:186\u2013195","journal-title":"Eng Appl Artif Intell"},{"key":"396_CR19","doi-asserted-by":"crossref","unstructured":"Zheng J, Zhou Y, Deng T et al. (2017) A self-trained semi supervised fuzzy clustering based on label propagation with variable weights. In: 29th Chinese control and decision conference (CCDC), Chongqing, China, pp. 7447\u20137452","DOI":"10.1109\/CCDC.2017.7978533"},{"key":"396_CR20","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.1007\/978-3-540-30499-9_191","volume-title":"International conference on neural information processing","author":"D Zhang","year":"2004","unstructured":"Zhang D, Tan K, Chen S et al (2004) Semi-supervised kernel-based fuzzy c-means. In: Pal NR, Kasabov N, Mudi RK, Pal S, Parui SK (eds) International conference on neural information processing. Springer, Berlin, pp 1229\u20131234"},{"key":"396_CR21","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.engappai.2017.11.007","volume":"68","author":"SD Mai","year":"2018","unstructured":"Mai SD, Ngo LT (2018) Multiple kernel approach to semi-supervised fuzzy clustering algorithm for land-cover classification. Eng Appl Artif Intell 68:205\u2013213","journal-title":"Eng Appl Artif Intell"},{"key":"396_CR22","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s12293-022-00369-6","volume":"14","author":"R Cheng","year":"2022","unstructured":"Cheng R, Ding JL, Du WL (2022) Thematic issue on knowledge and data driven evolutionary multi-objective optimization. Memetic Comput 14:133\u2013134","journal-title":"Memetic Comput"},{"key":"396_CR23","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.ins.2021.01.029","volume":"560","author":"HP Ma","year":"2021","unstructured":"Ma HP, Wei HY, Tian Y et al (2021) A multi-stage evolutionary algorithm for multi-objective optimization with complex constraints. Inf Sci 560:68\u201391","journal-title":"Inf Sci"},{"issue":"1","key":"396_CR24","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1109\/TEVC.2006.877146","volume":"11","author":"J Handl","year":"2007","unstructured":"Handl J, Knowles JD (2007) An evolutionary approach to multiobjective clustering. IEEE Trans Evol Comput 11(1):56\u201376","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"396_CR25","doi-asserted-by":"publisher","first-page":"872","DOI":"10.1016\/j.asoc.2010.01.007","volume":"11","author":"A Mukhopadhyay","year":"2011","unstructured":"Mukhopadhyay A, Maulik U (2011) A multiobjective approach to MR brain image segmentation. Appl Soft Comput 11(1):872\u2013880","journal-title":"Appl Soft Comput"},{"key":"396_CR26","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.asoc.2015.01.039","volume":"30","author":"F Zhao","year":"2015","unstructured":"Zhao F, Liu HQ, Fan JL (2015) A multiobjective spatial fuzzy clustering algorithm for image segmentation. Appl Soft Comput 30:48\u201357","journal-title":"Appl Soft Comput"},{"issue":"5","key":"396_CR27","first-page":"1106","volume":"41","author":"F Zhao","year":"2019","unstructured":"Zhao F, Zhang MM, Liu HQ (2019) Multi-objective evolutionary semi-supervised fuzzy clustering image segmentation motivated by region information. J Electron Inf Technol 41(5):1106\u20131113","journal-title":"J Electron Inf Technol"},{"key":"396_CR28","unstructured":"Li Z & Chen J (2015) Superpixel segmentation using linear spectral clustering. In: 2015 IEEE conference on computer vision and pattern recognition (CVPR), Boston, USA, pp. 1356\u20131363"},{"issue":"16","key":"396_CR29","doi-asserted-by":"publisher","first-page":"4186","DOI":"10.1016\/j.ijleo.2014.04.062","volume":"125","author":"Y Tong","year":"2014","unstructured":"Tong Y, Chen R, Cheng Y et al (2014) Facial expression recognition algorithm using LGC based on horizontal and diagonal prior principle. Optik 125(16):4186\u20134189","journal-title":"Optik"},{"issue":"2","key":"396_CR30","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1007\/s10489-018-1263-6","volume":"49","author":"Z Zhao","year":"2019","unstructured":"Zhao Z, Liu B, Zhang C et al (2019) An improved adaptive NSGA-II with multi-population algorithm. Appl Intell 49(2):569\u2013580","journal-title":"Appl Intell"},{"issue":"2","key":"396_CR31","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1109\/4235.996017","volume":"6","author":"K Deb","year":"2002","unstructured":"Deb K, Agrawal S, Pratap A et al (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):849\u2013858","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"396_CR32","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1016\/j.cviu.2007.08.003","volume":"110","author":"H Zhang","year":"2008","unstructured":"Zhang H, Fritts JE, Goldman SA (2008) Image segmentation evaluation: a survey of unsupervised methods. Comput Vis Image Underst 110(2):260\u2013280","journal-title":"Comput Vis Image Underst"},{"issue":"5","key":"396_CR33","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1109\/TPAMI.2010.161","volume":"33","author":"PA Arbelaez","year":"2011","unstructured":"Arbelaez PA, Maire M, Fowlkes CC et al (2011) Contour detection and hierarchical image segmentation. IEEE Trans Pattern Anal Mach Intell 33(5):898\u2013916","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"396_CR34","doi-asserted-by":"crossref","unstructured":"Cimpoi M, Maji S, Kokkinos I, et al. (2014) Describing textures in the wild. In: 2014 IEEE conference on computer vision and pattern recognition, Columbus, USA, pp. 3606\u20133613","DOI":"10.1109\/CVPR.2014.461"},{"key":"396_CR35","doi-asserted-by":"crossref","unstructured":"Yang Y, Newsam S (2010) Bag-of-visual-words and spatial extensions for land-use classification. In: ACM SIGSPATIAL international conference on advances in geographic information systems, San Jose California, pp. 270\u2013279","DOI":"10.1145\/1869790.1869829"},{"issue":"10","key":"396_CR36","doi-asserted-by":"publisher","first-page":"2044","DOI":"10.1016\/j.ins.2009.12.010","volume":"180","author":"S Garc\u00eda","year":"2010","unstructured":"Garc\u00eda S, Fern\u00e1ndez A, Luengo J, Herrera F (2010) Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: experimental analysis of power. Inf Sci 180(10):2044\u20132064","journal-title":"Inf Sci"}],"container-title":["Memetic Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12293-023-00396-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12293-023-00396-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12293-023-00396-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T02:13:43Z","timestamp":1701310423000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12293-023-00396-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,26]]},"references-count":36,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023,12]]}},"alternative-id":["396"],"URL":"https:\/\/doi.org\/10.1007\/s12293-023-00396-x","relation":{},"ISSN":["1865-9284","1865-9292"],"issn-type":[{"type":"print","value":"1865-9284"},{"type":"electronic","value":"1865-9292"}],"subject":[],"published":{"date-parts":[[2023,8,26]]},"assertion":[{"value":"18 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 August 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 August 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}