{"id":"https://openalex.org/W2290851631","doi":"https://doi.org/10.1109/siu.2015.7130372","title":"A comprehensive analysis of twin support vector machines in remote sensing image classification","display_name":"A comprehensive analysis of twin support vector machines in remote sensing image classification","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W2290851631","doi":"https://doi.org/10.1109/siu.2015.7130372","mag":"2290851631"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2015.7130372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2015.7130372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 23nd Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"},"type":"article","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/A5058660643","display_name":"G\u00fcl\u015fen Ta\u015fk\u0131n","orcid":"https://orcid.org/0000-0002-2294-4462"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"G. Taskin","raw_affiliation_strings":["Deprem M\u00fchendisli\u011fi ve Afet Y\u00f6netimi Enstit\u00fcs\u00fc, \u0130stanbul Teknik \u00dcniversitesi"],"affiliations":[{"raw_affiliation_string":"Deprem M\u00fchendisli\u011fi ve Afet Y\u00f6netimi Enstit\u00fcs\u00fc, \u0130stanbul Teknik \u00dcniversitesi","institution_ids":["https://openalex.org/I48912391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5058660643"],"corresponding_institution_ids":["https://openalex.org/I48912391"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.19522686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2427","last_page":"2429"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9830999970436096,"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":0.947080671787262},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7075300216674805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6825501918792725},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6653262376785278},{"id":"https://openalex.org/keywords/structured-support-vector-machine","display_name":"Structured support vector machine","score":0.6383935213088989},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5780676603317261},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5359467267990112},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5177440047264099},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5140129327774048},{"id":"https://openalex.org/keywords/linear-classifier","display_name":"Linear classifier","score":0.450851172208786},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.43098559975624084},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4103763997554779},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3516501784324646},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.26281341910362244}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.947080671787262},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7075300216674805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6825501918792725},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6653262376785278},{"id":"https://openalex.org/C125168437","wikidata":"https://www.wikidata.org/wiki/Q7625184","display_name":"Structured support vector machine","level":3,"score":0.6383935213088989},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5780676603317261},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5359467267990112},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5177440047264099},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5140129327774048},{"id":"https://openalex.org/C139532973","wikidata":"https://www.wikidata.org/wiki/Q2679259","display_name":"Linear classifier","level":3,"score":0.450851172208786},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.43098559975624084},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4103763997554779},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3516501784324646},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26281341910362244},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/siu.2015.7130372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2015.7130372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 23nd Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"},{"id":"pmh:oai:polen.itu.edu.tr:11527/35461","is_oa":false,"landing_page_url":"https://hdl.handle.net/11527/35461","pdf_url":null,"source":{"id":"https://openalex.org/S4306400460","display_name":"Istanbul Technical University Academic Open Archive (Istanbul Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I48912391","host_organization_name":"Istanbul Technical University","host_organization_lineage":["https://openalex.org/I48912391"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2069231281","https://openalex.org/W2090267913","https://openalex.org/W2132425109","https://openalex.org/W2170860445"],"related_works":["https://openalex.org/W2336974148","https://openalex.org/W3200179079","https://openalex.org/W3010923102","https://openalex.org/W2345184372","https://openalex.org/W2129101332","https://openalex.org/W2142674421","https://openalex.org/W1964761968","https://openalex.org/W2362981726","https://openalex.org/W1971675712","https://openalex.org/W1580929847"],"abstract_inverted_index":{"Recently,":[0],"a":[1,33],"supervised":[2],"classifier":[3],"called":[4],"twin":[5,43],"support":[6,20,44],"vector":[7,21,45],"machines":[8,22,46],"(twin-SVM)":[9],"has":[10,15,39],"been":[11,16,40],"introduced,":[12],"and":[13,84,135],"it":[14,38],"compared":[17,51],"to":[18,52,79,94,121,140],"classical":[19,66],"(SVM)":[23],"on":[24],"UCI":[25],"dataset":[26,152],"in":[27,90,92,155],"terms":[28],"of":[29,35,57,71,98,112,116,118,126,133,137],"classification":[30,49,123],"performance.":[31,142],"As":[32],"result":[34],"the":[36,69,99,109,122,141,144,156],"studies,":[37],"stated":[41],"that":[42],"provide":[47],"higher":[48],"performance":[50,86,97],"SVM.":[53,67,95],"The":[54,96],"main":[55],"advantage":[56],"using":[58],"twin-SVM":[59,74,128],"is":[60],"its":[61,85],"lower":[62],"computational":[63],"complexity":[64],"than":[65],"In":[68],"context":[70],"this":[72],"work,":[73],"will":[75,87,101,146],"be":[76,88,102,147],"firstly":[77],"applied":[78],"remote":[80,157],"sensing":[81,158],"image":[82],"classification,":[83],"analyzed":[89],"detail":[91],"comparison":[93],"method":[100],"evaluated":[103],"with":[104,130,149],"some":[105,150],"criteria":[106],"such":[107],"as":[108],"sensitivity":[110],"analysis":[111,125,145],"model":[113],"selection,":[114],"effects":[115,136],"number":[117],"training":[119],"samples":[120],"performance,":[124],"nonlinear":[127],"methods":[129],"different":[131],"type":[132],"kernels":[134],"feature":[138],"selection":[139],"All":[143],"conducted":[148],"benchmark":[151],"frequently":[153],"used":[154],"literature.":[159]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}