{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T21:42:05Z","timestamp":1757540525105,"version":"3.37.3"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T00:00:00Z","timestamp":1507852800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T00:00:00Z","timestamp":1507852800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61401493"],"award-info":[{"award-number":["61401493"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Ministries Foundation of China","award":["9140A01010415JB11002"],"award-info":[{"award-number":["9140A01010415JB11002"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2019,3,1]]},"DOI":"10.1007\/s13042-017-0732-2","type":"journal-article","created":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T12:36:17Z","timestamp":1507898177000},"page":"515-525","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A dynamic selection ensemble method for target recognition based on clustering and randomized reference classifier"],"prefix":"10.1007","volume":"10","author":[{"given":"Xueman","family":"Fan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengliang","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingbo","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,10,13]]},"reference":[{"issue":"3","key":"732_CR1","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1109\/34.667881","volume":"20","author":"J Kittler","year":"1998","unstructured":"Kittler J, Hatef M, Duin R P W, Matas J (1998) On combining classifiers. IEEE T Pattern Anal 20(3):226\u2013239","journal-title":"IEEE T Pattern Anal"},{"issue":"5","key":"732_CR2","doi-asserted-by":"publisher","first-page":"1638","DOI":"10.1109\/TFUZZ.2014.2371479","volume":"23","author":"XZ Wang","year":"2015","unstructured":"Wang XZ, Xing HJ, Li Y et al.(2015) A study on relationship between generalization abilities and fuzziness of base classifiers in ensemble learning. IEEE T Fuzzy Syst 23(5):1638\u20131654","journal-title":"IEEE T Fuzzy Syst"},{"key":"732_CR3","first-page":"178","volume-title":"Combining pattern classifiers: methods and algorithms","author":"IK Ludmila","year":"2014","unstructured":"Ludmila IK (2014) Combining pattern classifiers: methods and algorithms, 2nd\u00a0edn. Wiley, New York, pp\u00a0178\u2013183","edition":"2"},{"issue":"1","key":"732_CR4","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.inffus.2013.04.006","volume":"16","author":"M Wo\u017aniak","year":"2014","unstructured":"Wo\u017aniak M, Gra\u00f1a M, Corchado E (2014) A survey of multiple classifier systems as hybrid systems. Inf Fusion 16(1):3\u201317","journal-title":"Inf Fusion"},{"issue":"2","key":"732_CR5","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1109\/3477.990871","volume":"32","author":"LI Kuncheva","year":"2002","unstructured":"Kuncheva LI (2002) Switching between selection and fusion in combining classifiers: an experiment. IEEE T Syst Man Cybern 32(2):146\u2013156","journal-title":"IEEE T Syst Man Cybern"},{"key":"732_CR6","doi-asserted-by":"crossref","unstructured":"Azizi N, Farah N, Ennaji A (2012) New dynamic classifiers selection approach for handwritten recognition. In: Proceedings of international conference on artificial neural networks and machine learning, Springer, pp\u00a0189\u2013196","DOI":"10.1007\/978-3-642-33266-1_24"},{"issue":"C","key":"732_CR7","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1016\/j.asoc.2015.09.009","volume":"37","author":"R Mousavi","year":"2015","unstructured":"Mousavi R, Eftekhari M (2015) A new ensemble learning methodology based on hybridization of classifier ensemble selection approaches. Appl Soft Comput 37(C):652\u2013666","journal-title":"Appl Soft Comput"},{"issue":"11","key":"732_CR8","doi-asserted-by":"publisher","first-page":"3665","DOI":"10.1016\/j.patcog.2014.05.003","volume":"47","author":"AS Britto","year":"2014","unstructured":"Britto AS, Sabourin R, Oliveira L E S (2014) Dynamic selection of classifiers\u2014a comprehensive review. Pattern Recogn 47(11):3665\u20133680","journal-title":"Pattern Recogn"},{"issue":"5","key":"732_CR9","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1016\/j.patcog.2007.10.015","volume":"41","author":"AH Ko","year":"2008","unstructured":"Ko AH, Sabourin R, Britto AS (2008) From dynamic classifier selection to dynamic ensemble selection. Pattern Recogn 41(5):1735\u20131748","journal-title":"Pattern Recogn"},{"issue":"3\u20134","key":"732_CR10","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1007\/s00521-011-0737-9","volume":"22","author":"PR Cavalin","year":"2013","unstructured":"Cavalin PR, Sabourin R, Suen CY (2013) Dynamic selection approaches for multiple classifier systems. Neural Comput Appl 22(3\u20134):673\u2013688","journal-title":"Neural Comput Appl"},{"key":"732_CR11","doi-asserted-by":"crossref","unstructured":"Cruz R M O, Cavalcanti G D C, Ren TI (2011) A method for dynamic ensemble selection based on a filter and an adaptive distance to improve the quality of the regions of competence. In: Proceedings of International Joint Conference on Neural Networks, IEEE, pp\u00a01126\u20131133","DOI":"10.1109\/IJCNN.2011.6033350"},{"issue":"1","key":"732_CR12","first-page":"98","volume":"142","author":"N Azizi","year":"2015","unstructured":"Azizi N, Farah N, Khadir T (2015) Multi stage dynamic ensemble selection using heterogeneous learning algorithms: application on classification problems. Int J Knowl Manag Stud 142(1):98\u2013104","journal-title":"Int J Knowl Manag Stud"},{"issue":"10","key":"732_CR13","doi-asserted-by":"publisher","first-page":"2993","DOI":"10.1016\/j.patcog.2008.03.027","volume":"41","author":"EMD Santos","year":"2008","unstructured":"Santos E M D, Sabourin R, Maupin P (2008) A dynamic overproduce-and-choose strategy for the selection of classifier ensembles. Pattern Recogn 41(10):2993\u20133009","journal-title":"Pattern Recogn"},{"issue":"9","key":"732_CR14","doi-asserted-by":"publisher","first-page":"1879","DOI":"10.1016\/S0031-3203(00)00150-3","volume":"34","author":"G Giacinto","year":"2001","unstructured":"Giacinto G, Roli F (2001) Dynamic classifier selection based on multiple classifier behavior. Pattern Recogn 34(9):1879\u20131881","journal-title":"Pattern Recogn"},{"key":"732_CR15","unstructured":"Krijthe JH, Ho TK, Loog M (2012) Improving cross-validation based classifier selection using meta-learning. In: Proceedings of international conference on pattern recognition, IEEE, pp\u00a02873\u20132876"},{"issue":"5","key":"732_CR16","doi-asserted-by":"publisher","first-page":"1925","DOI":"10.1016\/j.patcog.2014.12.003","volume":"48","author":"RM Cruz","year":"2015","unstructured":"Cruz RM, Sabourin R, Cavalcanti GDC et al.(2015) META-DES: A dynamic ensemble selection framework using meta-learning. Pattern Recogn 48(5):1925\u20131935","journal-title":"Pattern Recogn"},{"issue":"10\u201311","key":"732_CR17","doi-asserted-by":"publisher","first-page":"2656","DOI":"10.1016\/j.patcog.2011.03.020","volume":"44","author":"T Woloszynski","year":"2011","unstructured":"Woloszynski T, Kurzynski M (2011) A probabilistic model of classifier competence for dynamic ensemble selection. Pattern Recogn 44(10\u201311):2656\u20132668","journal-title":"Pattern Recogn"},{"key":"732_CR18","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.patcog.2015.08.015","volume":"50","author":"D Huang","year":"2016","unstructured":"Huang D, Lai JH, Wang CD (2016) Ensemble clustering using factor graph. Pattern Recognition Pattern Recogn 50:131\u2013142","journal-title":"Pattern Recognition Pattern Recogn"},{"issue":"5","key":"732_CR19","doi-asserted-by":"publisher","first-page":"1312","DOI":"10.1109\/TKDE.2015.2503753","volume":"28","author":"D Huang","year":"2016","unstructured":"Huang D, Lai JH, Wang CD (2016) Robust ensemble clustering using probability trajectories. IEEE T Knowl Data Eng 28(5):1312\u20131326","journal-title":"IEEE T Knowl Data Eng"},{"key":"732_CR20","doi-asserted-by":"crossref","unstructured":"Zenobi G, Cunningham P (2001) Using Diversity in Preparing Ensembles of Classifiers Based on Different Feature Subsets to Minimize Generalization Error. In: Proceedings of European conference on machine learning, Springe, pp\u00a0576\u2013587","DOI":"10.1007\/3-540-44795-4_49"},{"issue":"4","key":"732_CR21","doi-asserted-by":"publisher","first-page":"472","DOI":"10.1016\/j.patrec.2006.09.001","volume":"28","author":"AMP Canuto","year":"2007","unstructured":"Canuto AMP, Abreu MCC, Oliveira LDM et al.(2007) Investigating the influence of the choice of the ensemble members in accuracy and diversity of selection-based and fusion-based methods for ensembles. Pattern Recogn Lett 28(4):472\u2013486","journal-title":"Pattern Recogn Lett"},{"issue":"3","key":"732_CR22","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1016\/j.inffus.2011.03.007","volume":"13","author":"T Woloszynski","year":"2012","unstructured":"Woloszynski T, Kurzynski M, Podsiadlo P et al.(2012) A measure of competence based on random classification for dynamic ensemble selection. Inf Fusion 13(3):207\u2013213","journal-title":"Inf Fusion"},{"key":"732_CR23","unstructured":"Cameron WL, Leung LK (1990) Feature motivated polarization scattering matrix decomposition. In: Proceedings of international conference on radar, IEEE, pp\u00a0549\u2013557"},{"issue":"10","key":"732_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2016.2594250","volume":"54","author":"Y Chen","year":"2016","unstructured":"Chen Y, Jiang H, Li C, Jia X (2016) Deep feature extraction and classification of hyperspectral images based on convolutional neural networks. IEEE T Geosci Rem 54(10):1\u201320","journal-title":"IEEE T Geosci Rem"},{"issue":"4","key":"732_CR25","doi-asserted-by":"publisher","first-page":"2558","DOI":"10.1109\/TAES.2011.6034651","volume":"47","author":"CM Pilcher","year":"2011","unstructured":"Pilcher CM, Khotanzad A (2011) Maritime ATR using classifier combination and high resolution range profiles. IEEE Trans Aerosp Electron Syst 47(4):2558\u20132573","journal-title":"IEEE Trans Aerosp Electron Syst"},{"issue":"1","key":"732_CR26","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1109\/36.551935","volume":"35","author":"SR Cloude","year":"1997","unstructured":"Cloude SR, Pottier E (1997) An entropy based classification scheme for land applications of polarimetric SAR. IEEE T Geosci Remote 35(1):68\u201378","journal-title":"IEEE T Geosci Remote"},{"key":"732_CR27","unstructured":"Berizzi F, Martorella M, Capria A et al.(2008) H\/\u03b1 polarimetric features for man-made target classification. In: Proceedings of international conference on radar conference, IEEE, pp\u00a01\u20136"},{"issue":"6","key":"732_CR28","first-page":"861","volume":"28","author":"L Lei","year":"2013","unstructured":"Lei L, Wang XD, Xing YQ et al.(2013) Multi-polarized HRRP classification by SVM and DS evidence theory. Control Decis 28(6):861\u2013866 (Chinese)","journal-title":"Control Decis"},{"key":"732_CR29","unstructured":"Guo L (2009) Wideband radar target polarimetric feature extraction and recognition method based on kernel method. Dissertation, National University of Defense Technology. (in chinese)"},{"issue":"12","key":"732_CR30","first-page":"3261","volume":"38","author":"XM Fan","year":"2016","unstructured":"Fan XM, Hu SL, He JB (2016) Feature extraction and selection of Full Polarization HRRP in the target recognition process of maritime surveillance radar. J Electrs Inf Technol 38(12):3261\u20133268","journal-title":"J Electrs Inf Technol"},{"issue":"4","key":"732_CR31","doi-asserted-by":"publisher","first-page":"556","DOI":"10.1109\/34.993562","volume":"24","author":"DS Yeung","year":"2002","unstructured":"Yeung DS, Wang XZ (2002) Improving performance of similarity-based clustering by feature weight learning. IEEE T Pattern Anal 24(4):556\u2013561","journal-title":"IEEE T Pattern Anal"},{"issue":"1","key":"732_CR32","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1007\/s10994-006-9449-2","volume":"65","author":"EK Tang","year":"2006","unstructured":"Tang EK, Suganthan PN, Yao X (2006) An analysis of diversity measures. Mach Learn 65(1):247\u2013271","journal-title":"Mach Learn"},{"key":"732_CR33","first-page":"7","volume":"1","author":"RC Balabantaray","year":"2015","unstructured":"Balabantaray RC, Sarma C, Jha M (2015) Document clustering using K-means and K-medoids. Int J Knowl Based Comput Syst 1:7\u201313","journal-title":"Int J Knowl Based Comput Syst"},{"key":"732_CR34","first-page":"279","volume-title":"From static to dynamic ensemble of classifiers selection: application to Arabic handwritten recognition","author":"N Azizi","year":"2012","unstructured":"Azizi N, Farah N (2012) From static to dynamic ensemble of classifiers selection: application to Arabic handwritten recognition. IOS press, USA, pp\u00a0279\u2013288"},{"issue":"1","key":"732_CR35","first-page":"1","volume":"7","author":"J Demsar","year":"2015","unstructured":"Demsar J (2015) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7(1):1\u201330","journal-title":"J Mach Learn Res"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-017-0732-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-017-0732-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-017-0732-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,19]],"date-time":"2021-02-19T21:58:23Z","timestamp":1613771903000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-017-0732-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,13]]},"references-count":35,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2019,3,1]]}},"alternative-id":["732"],"URL":"https:\/\/doi.org\/10.1007\/s13042-017-0732-2","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2017,10,13]]},"assertion":[{"value":"11 November 2016","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 October 2017","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2017","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}