{"id":"https://openalex.org/W3118697419","doi":"https://doi.org/10.1109/siu49456.2020.9302178","title":"Metric Learning with Quadruplets on Non-Hierarchical Labeled Datasets","display_name":"Metric Learning with Quadruplets on Non-Hierarchical Labeled Datasets","publication_year":2020,"publication_date":"2020-10-05","ids":{"openalex":"https://openalex.org/W3118697419","doi":"https://doi.org/10.1109/siu49456.2020.9302178","mag":"3118697419"},"language":"en","primary_location":{"id":"doi:10.1109/siu49456.2020.9302178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu49456.2020.9302178","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","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/A5072454178","display_name":"Kaan Karaman","orcid":null},"institutions":[{"id":"https://openalex.org/I201799495","display_name":"Middle East Technical University","ror":"https://ror.org/014weej12","country_code":"TR","type":"education","lineage":["https://openalex.org/I201799495"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Kaan Karaman","raw_affiliation_strings":["METU,Electrical and Electronics Eng. Dept.,Ankara,Turkey","Electrical and Electronics Eng. Dept., METU, Ankara, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"METU,Electrical and Electronics Eng. Dept.,Ankara,Turkey","institution_ids":["https://openalex.org/I201799495"]},{"raw_affiliation_string":"Electrical and Electronics Eng. Dept., METU, Ankara, Turkey","institution_ids":["https://openalex.org/I201799495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064965216","display_name":"\u0130brahim Batuhan Akkaya","orcid":"https://orcid.org/0000-0003-2663-846X"},"institutions":[{"id":"https://openalex.org/I201799495","display_name":"Middle East Technical University","ror":"https://ror.org/014weej12","country_code":"TR","type":"education","lineage":["https://openalex.org/I201799495"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"\u0130brahim Batuhan Akkaya","raw_affiliation_strings":["METU,Electrical and Electronics Eng. Dept.,Ankara,Turkey","Electrical and Electronics Eng. Dept., METU, Ankara, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"METU,Electrical and Electronics Eng. Dept.,Ankara,Turkey","institution_ids":["https://openalex.org/I201799495"]},{"raw_affiliation_string":"Electrical and Electronics Eng. Dept., METU, Ankara, Turkey","institution_ids":["https://openalex.org/I201799495"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070112256","display_name":"A. Ayd\u0131n Alatan","orcid":"https://orcid.org/0000-0001-5556-7301"},"institutions":[{"id":"https://openalex.org/I201799495","display_name":"Middle East Technical University","ror":"https://ror.org/014weej12","country_code":"TR","type":"education","lineage":["https://openalex.org/I201799495"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"A. Ayd\u0131n Alatan","raw_affiliation_strings":["METU,Electrical and Electronics Eng. Dept.,Ankara,Turkey","Electrical and Electronics Eng. Dept., METU, Ankara, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"METU,Electrical and Electronics Eng. Dept.,Ankara,Turkey","institution_ids":["https://openalex.org/I201799495"]},{"raw_affiliation_string":"Electrical and Electronics Eng. Dept., METU, Ankara, Turkey","institution_ids":["https://openalex.org/I201799495"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I201799495"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9973000288009644,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9973000288009644,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9908999800682068,"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"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9817000031471252,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/quadruplets","display_name":"Quadruplets","score":0.9353275895118713},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.7909395098686218},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7409671545028687},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6980000734329224},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5365680456161499},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5059613585472107},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49956345558166504},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.41578441858291626}],"concepts":[{"id":"https://openalex.org/C2910608164","wikidata":"https://www.wikidata.org/wiki/Q25671","display_name":"Quadruplets","level":4,"score":0.9353275895118713},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7909395098686218},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7409671545028687},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6980000734329224},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5365680456161499},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5059613585472107},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49956345558166504},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.41578441858291626},{"id":"https://openalex.org/C2779234561","wikidata":"https://www.wikidata.org/wiki/Q11995","display_name":"Pregnancy","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C46973012","wikidata":"https://www.wikidata.org/wiki/Q28627","display_name":"Gestation","level":3,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu49456.2020.9302178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu49456.2020.9302178","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W219040644","https://openalex.org/W1509966554","https://openalex.org/W2117539524","https://openalex.org/W2127589108","https://openalex.org/W2138621090","https://openalex.org/W2194775991","https://openalex.org/W2895347732","https://openalex.org/W2899771611","https://openalex.org/W2962898354","https://openalex.org/W2963713828","https://openalex.org/W2969656782","https://openalex.org/W2970045865","https://openalex.org/W3099206234"],"related_works":["https://openalex.org/W2405349220","https://openalex.org/W2460818900","https://openalex.org/W2242452831","https://openalex.org/W2771384155","https://openalex.org/W2124520329","https://openalex.org/W2473097741","https://openalex.org/W3030305499","https://openalex.org/W2125229622","https://openalex.org/W1997985403","https://openalex.org/W2113252685"],"abstract_inverted_index":{"Metric":[0],"learning":[1,44],"is":[2,39,46,89,110,138,174,206],"a":[3,108,187],"frequently":[4],"utilized":[5],"method":[6,27,173],"that":[7,131,137,163,183],"can":[8,128],"be":[9,129],"applied":[10],"to":[11,102,154,176],"many":[12],"different":[13,94,196],"computer":[14],"vision":[15],"problems":[16],"and;":[17],"thus,":[18],"facilitates":[19],"these":[20],"problems.":[21],"In":[22,168],"this":[23,169],"paper,":[24,170],"the":[25,30,34,42,51,63,72,86,99,119,135,156,165,178,192,210,215],"proposed":[26,97,175,216],"for":[28,106],"manipulating":[29],"feature":[31],"space":[32],"with":[33,48,140],"help":[35],"of":[36,41,65,122,194,214],"quadruplets,":[37],"which":[38],"one":[40],"metric":[43,66],"methods,":[45],"explained":[47],"details,":[49],"and":[50,74,77,93,124,202,212],"results":[52,79],"obtained":[53,82],"by":[54,83,116,208],"using":[55],"it":[56,127,152],"are":[57,96,200],"shown.":[58],"Many":[59],"methods":[60,121,199],"used":[61],"in":[62,98,134,181],"field":[64],"learning,":[67],"have":[68,80,144,164,186],"been":[69,81],"developed":[70],"on":[71,160],"Siamese":[73,123],"triplet":[75,125],"structures":[76],"satisfactory":[78],"them.":[84],"Similarly,":[85],"quadruplet":[87,109,141,157,179,197],"structure":[88,158,180],"still":[90],"being":[91],"studied":[92],"approaches":[95],"literature.":[100],"How":[101],"select":[103],"four":[104],"elements":[105],"generating":[107],"not":[111,185],"standardized":[112],"at":[113,118,145],"present.":[114],"However,":[115],"looking":[117],"mining":[120,198],"samples,":[126,142],"concluded":[130],"each":[132],"sample":[133],"dataset":[136],"trained":[139],"must":[143],"least":[146],"two":[147],"hierarchical":[148,166,188],"labels.":[149,167],"This":[150],"makes":[151],"possible":[153],"train":[155],"only":[159],"certain":[161],"datasets":[162,182],"an":[171,203],"unsupervised":[172],"use":[177],"do":[184],"label":[189],"structure.":[190],"Besides,":[191],"performances":[193],"three":[195],"compared":[201],"ablation":[204],"study":[205],"conducted":[207],"discussing":[209],"advantages":[211],"disadvantages":[213],"method.":[217]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}