{"id":"https://openalex.org/W1964603962","doi":"https://doi.org/10.1109/iccvw.2009.5457713","title":"Large margin classifiers based on convex class models","display_name":"Large margin classifiers based on convex class models","publication_year":2009,"publication_date":"2009-09-01","ids":{"openalex":"https://openalex.org/W1964603962","doi":"https://doi.org/10.1109/iccvw.2009.5457713","mag":"1964603962"},"language":"en","primary_location":{"id":"doi:10.1109/iccvw.2009.5457713","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw.2009.5457713","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072358879","display_name":"Hakan \u00c7ev\u0131kalp","orcid":"https://orcid.org/0000-0002-1708-8817"},"institutions":[{"id":"https://openalex.org/I51209816","display_name":"Eski\u015fehir Osmangazi University","ror":"https://ror.org/01dzjez04","country_code":"TR","type":"education","lineage":["https://openalex.org/I51209816"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Hakan Cevikalp","raw_affiliation_strings":["Eskisehir Osmangazi University, Eskisehir, Turkey","Eskisehir Osmangazi University, Meselik Kampusu, 26480, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eskisehir Osmangazi University, Eskisehir, Turkey","institution_ids":["https://openalex.org/I51209816"]},{"raw_affiliation_string":"Eskisehir Osmangazi University, Meselik Kampusu, 26480, Turkey","institution_ids":["https://openalex.org/I51209816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062363302","display_name":"Bill Triggs","orcid":"https://orcid.org/0000-0003-4116-6296"},"institutions":[{"id":"https://openalex.org/I4210149092","display_name":"Laboratoire Jean Kuntzmann","ror":"https://ror.org/04ett5b41","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210149092","https://openalex.org/I899635006","https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Bill Triggs","raw_affiliation_strings":["Laboratoire Jean Kuntzmann, Grenoble, France","Laboratoire Jean Kuntzmann, B.P. 53, 38041 Grenoble Cedex 9, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire Jean Kuntzmann, Grenoble, France","institution_ids":["https://openalex.org/I4210149092"]},{"raw_affiliation_string":"Laboratoire Jean Kuntzmann, B.P. 53, 38041 Grenoble Cedex 9, France","institution_ids":["https://openalex.org/I4210149092"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"101","last_page":"108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6959925889968872},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6612705588340759},{"id":"https://openalex.org/keywords/convex-hull","display_name":"Convex hull","score":0.6316999197006226},{"id":"https://openalex.org/keywords/affine-hull","display_name":"Affine hull","score":0.630454957485199},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6023937463760376},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5603978633880615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5453751087188721},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.5178278088569641},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5108625292778015},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5063053369522095},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.47859880328178406},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.46754518151283264},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4574853479862213},{"id":"https://openalex.org/keywords/margin-classifier","display_name":"Margin classifier","score":0.4510643780231476},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4419425427913666},{"id":"https://openalex.org/keywords/orthonormal-basis","display_name":"Orthonormal basis","score":0.4239889681339264},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.38581955432891846},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.256160706281662},{"id":"https://openalex.org/keywords/affine-space","display_name":"Affine space","score":0.20327287912368774}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6959925889968872},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6612705588340759},{"id":"https://openalex.org/C206194317","wikidata":"https://www.wikidata.org/wiki/Q1138624","display_name":"Convex hull","level":3,"score":0.6316999197006226},{"id":"https://openalex.org/C112128483","wikidata":"https://www.wikidata.org/wiki/Q382504","display_name":"Affine hull","level":4,"score":0.630454957485199},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6023937463760376},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5603978633880615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5453751087188721},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.5178278088569641},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5108625292778015},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5063053369522095},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.47859880328178406},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.46754518151283264},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4574853479862213},{"id":"https://openalex.org/C173102733","wikidata":"https://www.wikidata.org/wiki/Q6760396","display_name":"Margin classifier","level":3,"score":0.4510643780231476},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4419425427913666},{"id":"https://openalex.org/C5806529","wikidata":"https://www.wikidata.org/wiki/Q2365325","display_name":"Orthonormal basis","level":2,"score":0.4239889681339264},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.38581955432891846},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.256160706281662},{"id":"https://openalex.org/C173110770","wikidata":"https://www.wikidata.org/wiki/Q382698","display_name":"Affine space","level":3,"score":0.20327287912368774},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccvw.2009.5457713","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw.2009.5457713","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322628","display_name":"T\u00fcrkiye Bilimler Akademisi","ror":"https://ror.org/00aqt9352"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1494123191","https://openalex.org/W1564660545","https://openalex.org/W1970088130","https://openalex.org/W2040672759","https://openalex.org/W2053090063","https://openalex.org/W2109724208","https://openalex.org/W2119821739","https://openalex.org/W2130491779","https://openalex.org/W2139212933","https://openalex.org/W2140095548","https://openalex.org/W2151103935","https://openalex.org/W2153509747","https://openalex.org/W2157239837","https://openalex.org/W2158019970","https://openalex.org/W2161358738","https://openalex.org/W2163802728","https://openalex.org/W2994340921","https://openalex.org/W3123099834","https://openalex.org/W4239510810","https://openalex.org/W6629651395","https://openalex.org/W6635552349","https://openalex.org/W6683380652","https://openalex.org/W6683573406"],"related_works":["https://openalex.org/W2888937984","https://openalex.org/W2407804800","https://openalex.org/W2125266525","https://openalex.org/W2100597930","https://openalex.org/W2056148169","https://openalex.org/W2973367007","https://openalex.org/W1527337518","https://openalex.org/W2128012032","https://openalex.org/W2163821662","https://openalex.org/W2149131139"],"abstract_inverted_index":{"We":[0,149],"propose":[1],"large":[2],"margin":[3,61,117],"classifiers":[4,118,162],"that":[5,58,76,168],"are":[6,90,110,170],"sometimes":[7],"better":[8],"than":[9],"Support":[10],"Vector":[11],"Machines":[12],"(SVMs)":[13],"for":[14],"high-dimensional":[15],"classification":[16],"problems":[17],"with":[18,32,92,173],"limited":[19],"numbers":[20],"of":[21,36,47,49,81,96,141],"training":[22,42,147],"samples.":[23,43,148],"The":[24],"basic":[25],"idea":[26],"is":[27,53,101],"to":[28,155,158],"approximate":[29],"each":[30],"class":[31],"a":[33,54,73],"convex":[34,74,94,108],"model":[35],"some":[37],"form":[38],"based":[39,119],"on":[40,120,138,163],"its":[41],"For":[44],"any":[45],"pair":[46,80],"models":[48,109],"this":[50,66],"form,":[51],"there":[52],"corresponding":[55,160],"linear":[56],"classifier":[57],"maximizes":[59],"the":[60,63,78,84,88,93,99,102,139,146,151,159],"between":[62],"models,":[64],"and":[65,123,157],"can":[67,129],"be":[68,131],"found":[69],"efficiently":[70],"by":[71,133,145],"solving":[72],"program":[75],"finds":[77],"closest":[79],"points":[82],"in":[83,135],"two":[85],"sets.":[86],"If":[87],"classes":[89],"modeled":[91],"hulls":[95],"their":[97],"samples":[98],"result":[100],"standard":[103],"SVM,":[104],"but":[105],"many":[106],"other":[107],"possible.":[111],"As":[112],"examples":[113],"we":[114],"investigate":[115],"maximum":[116],"affine":[121],"hull":[122],"bounding":[124],"hyperdisk":[125],"models.":[126],"These":[127],"methods":[128,154],"also":[130],"kernelized":[132],"working":[134],"orthonormal":[136],"coordinates":[137],"subspace":[140],"feature":[142],"space":[143],"spanned":[144],"compare":[150],"resulting":[152],"margin-between-convex-model":[153],"SVM":[156],"nearest-convex-model":[161],"several":[164],"data":[165],"sets,":[166],"showing":[167],"they":[169],"often":[171],"competitive":[172],"these":[174],"well-established":[175],"approaches.":[176]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}