{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T02:02:18Z","timestamp":1780538538582,"version":"3.54.1"},"reference-count":41,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100004541","name":"Ministry of Education, India","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004541","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Sciences"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.ins.2026.123557","type":"journal-article","created":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T06:30:22Z","timestamp":1777271422000},"page":"123557","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Granular ball twin bounded support vector machine with generalized pinball loss"],"prefix":"10.1016","volume":"751","author":[{"given":"Nikita","family":"Grewal","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2613-6806","authenticated-orcid":false,"given":"S.K.","family":"Gupta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7728-3668","authenticated-orcid":false,"given":"Sanjeev","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ins.2026.123557_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2023.102059","article-title":"Fundus-DeepNet: multi-label deep learning classification system for enhanced detection of multiple ocular diseases through data fusion of fundus images","volume":"102","author":"Al-Fahdawi","year":"2024","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.ins.2026.123557_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.128116","article-title":"Enhanced multi-grade diabetic retinopathy detection and classification via ensembled deep learning model from retinal fundus images","volume":"285","author":"Hariobulesu","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.ins.2026.123557_bib0015","doi-asserted-by":"crossref","first-page":"79793","DOI":"10.1109\/ACCESS.2025.3566073","article-title":"EffNet-SVM: a hybrid model for diabetic retinopathy classification using retinal fundus images","volume":"13","author":"Naveen","year":"2025","journal-title":"IEEE Access"},{"key":"10.1016\/j.ins.2026.123557_bib0020","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-025-99309-w","article-title":"A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images","volume":"15","author":"Sushith","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.ins.2026.123557_bib0025","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1023\/A:1022627411411","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"10.1016\/j.ins.2026.123557_bib0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2022.104687","article-title":"Multi-category intuitionistic fuzzy twin support vector machines with an application to plant leaf recognition","volume":"110","author":"Laxmi","year":"2022","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.ins.2026.123557_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.109450","article-title":"Brain tumor classification using weighted least square twin support vector machine with fuzzy hyperplane","volume":"138","author":"Arora","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.ins.2026.123557_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.111816","article-title":"Intuitionistic fuzzy twin proximal SVM with fuzzy hyperplane and its application in EEG signal classification","volume":"163","author":"Arora","year":"2024","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.ins.2026.123557_bib0045","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.psep.2024.10.045","article-title":"Divisional intuitionistic fuzzy least squares twin SVM for pipeline leakage detection","volume":"192","author":"Dai","year":"2024","journal-title":"Process Saf. Environ. Prot."},{"key":"10.1016\/j.ins.2026.123557_bib0050","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1109\/TPAMI.2007.1068","article-title":"Twin support vector machines for pattern classification","volume":"29","author":"Khemchandani","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.ins.2026.123557_bib0055","doi-asserted-by":"crossref","first-page":"962","DOI":"10.1109\/TNN.2011.2130540","article-title":"Improvements on twin support vector machines","volume":"22","author":"Shao","year":"2011","journal-title":"IEEE Trans. Neural Netw."},{"key":"10.1016\/j.ins.2026.123557_bib0060","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1023\/A:1018628609742","article-title":"Least squares support vector machine classifiers","volume":"9","author":"Suykens","year":"1999","journal-title":"Neural Process. Lett."},{"key":"10.1016\/j.ins.2026.123557_bib0065","doi-asserted-by":"crossref","first-page":"7535","DOI":"10.1016\/j.eswa.2008.09.066","article-title":"Least squares twin support vector machines for pattern classification","volume":"36","author":"Kumar","year":"2009","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.ins.2026.123557_bib0070","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.knosys.2013.01.008","article-title":"Structural twin support vector machine for classification","volume":"43","author":"Qi","year":"2013","journal-title":"Knowl.-based Syst."},{"key":"10.1016\/j.ins.2026.123557_bib0075","article-title":"A weighted least squares twin support vector machine","volume":"30","author":"Xu","year":"2014","journal-title":"J. Inf. Sci. Eng."},{"key":"10.1016\/j.ins.2026.123557_bib0080","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.neucom.2019.09.069","article-title":"\u03bd-projection twin support vector machine for pattern classification","volume":"376","author":"Chen","year":"2020","journal-title":"Neurocomputing"},{"key":"10.1016\/j.ins.2026.123557_bib0085","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2024.121798","article-title":"Robust least squares twin bounded support vector machine with a generalized correntropy-induced metric","volume":"699","author":"Yuan","year":"2025","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2026.123557_bib0090","doi-asserted-by":"crossref","first-page":"984","DOI":"10.1109\/TPAMI.2013.178","article-title":"Support vector machine classifier with pinball loss","volume":"36","author":"Huang","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.ins.2026.123557_bib0095","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1257\/jep.15.4.143","article-title":"Quantile regression","volume":"15","author":"Koenker","year":"2001","journal-title":"J. Econ. Perspect."},{"key":"10.1016\/j.ins.2026.123557_bib0100","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1109\/TNNLS.2015.2513006","article-title":"A novel twin support-vector machine with pinball loss","volume":"28","author":"Xu","year":"2016","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.ins.2026.123557_bib0105","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.ins.2019.04.032","article-title":"General twin support vector machine with pinball loss function","volume":"494","author":"Tanveer","year":"2019","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2026.123557_bib0110","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.neucom.2018.08.079","article-title":"Generalized pinball loss SVMs","volume":"322","author":"Rastogi","year":"2018","journal-title":"Neurocomputing"},{"key":"10.1016\/j.ins.2026.123557_bib0115","doi-asserted-by":"crossref","first-page":"289","DOI":"10.3390\/sym14020289","article-title":"A novel twin support vector machine with generalized pinball loss function for pattern classification","volume":"14","author":"Panup","year":"2022","journal-title":"Symmetry"},{"key":"10.1016\/j.ins.2026.123557_bib0120","doi-asserted-by":"crossref","first-page":"18729","DOI":"10.1002\/mma.9588","article-title":"A novel support vector machine with generalized pinball loss for uncertain data classification","volume":"46","author":"Damminsed","year":"2023","journal-title":"Math. Methods Appl. Sci."},{"key":"10.1016\/j.ins.2026.123557_bib0125","doi-asserted-by":"crossref","first-page":"11684","DOI":"10.1007\/s11227-023-05082-w","article-title":"Smooth support vector machine with generalized pinball loss for pattern classification","volume":"79","author":"Makmuang","year":"2023","journal-title":"The Journal of Supercomputing"},{"key":"10.1016\/j.ins.2026.123557_bib0130","series-title":"Proceedings of IEEE 5th International Fuzzy Systems","first-page":"1","article-title":"Key roles of information granulation and fuzzy logic in human reasoning, concept formulation and computing with words","volume":"vol. 1","author":"Zadeh","year":"1996"},{"key":"10.1016\/j.ins.2026.123557_bib0135","series-title":"Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security","first-page":"44","article-title":"Granular computing for data mining","volume":"vol. 6241","author":"Yao","year":"2006"},{"key":"10.1016\/j.ins.2026.123557_bib0140","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.ins.2019.01.010","article-title":"Granular ball computing classifiers for efficient, scalable and robust learning","volume":"483","author":"Xia","year":"2019","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2026.123557_bib0145","doi-asserted-by":"crossref","first-page":"12444","DOI":"10.1109\/TNNLS.2024.3476391","article-title":"Granular ball twin support vector machine","volume":"36","author":"Quadir","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.ins.2026.123557_bib0150","doi-asserted-by":"crossref","first-page":"3891","DOI":"10.1109\/TCSS.2024.3411395","article-title":"Granular ball twin support vector machine with pinball loss function","volume":"12","author":"Quadir","year":"2025","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"key":"10.1016\/j.ins.2026.123557_bib0155","series-title":"Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond","author":"Sch\u00f6lkopf","year":"2002"},{"key":"10.1016\/j.ins.2026.123557_bib0160","first-page":"1071","article-title":"Sparseness of support vector machines","volume":"4","author":"Steinwart","year":"2003","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.ins.2026.123557_bib0165","first-page":"1007","article-title":"On robustness properties of convex risk minimization methods for pattern recognition","volume":"5","author":"Christmann","year":"2004","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.ins.2026.123557_bib0170","author":"Xia"},{"key":"10.1016\/j.ins.2026.123557_bib0175","article-title":"TRKM: twin restricted kernel machines for classification and regression","author":"Quadir","year":"2025","journal-title":"Neural Netw."},{"key":"10.1016\/j.ins.2026.123557_bib0180","first-page":"255","article-title":"KEEL data-mining software tool: data set repository, integration of algorithms and experimental analysis framework","volume":"17","author":"Derrac","year":"2015","journal-title":"J. Mult.-Valued Log. Soft Comput."},{"key":"10.1016\/j.ins.2026.123557_bib0185","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data sets","volume":"7","author":"Dem\u0161ar","year":"2006","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.ins.2026.123557_bib0190","author":"Doddi"},{"key":"10.1016\/j.ins.2026.123557_bib0195","article-title":"Ten deep learning techniques to address small data problems with remote sensing","volume":"125","author":"Safonova","year":"2023","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.ins.2026.123557_bib0200","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1007\/s11425-010-0018-6","article-title":"The new interpretation of support vector machines on statistical learning theory","volume":"53","author":"Zhang","year":"2010","journal-title":"Science in China Series A: Mathematics"},{"key":"10.1016\/j.ins.2026.123557_bib0205","series-title":"The Nature of Statistical Learning Theory","author":"Vapnik","year":"1999"}],"container-title":["Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0020025526004883?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0020025526004883?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T01:00:11Z","timestamp":1780534811000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0020025526004883"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":41,"alternative-id":["S0020025526004883"],"URL":"https:\/\/doi.org\/10.1016\/j.ins.2026.123557","relation":{},"ISSN":["0020-0255"],"issn-type":[{"value":"0020-0255","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Granular ball twin bounded support vector machine with generalized pinball loss","name":"articletitle","label":"Article Title"},{"value":"Information Sciences","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ins.2026.123557","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"123557"}}