{"id":"https://openalex.org/W2863314949","doi":"https://doi.org/10.1109/siu.2018.8404227","title":"Variational autoencoders with triplet loss for representation learning","display_name":"Variational autoencoders with triplet loss for representation learning","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2863314949","doi":"https://doi.org/10.1109/siu.2018.8404227","mag":"2863314949"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2018.8404227","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2018.8404227","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th 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/A5048675456","display_name":"\u00c7a\u011fatay I\u015f\u0131l","orcid":"https://orcid.org/0000-0003-3367-1858"},"institutions":[{"id":"https://openalex.org/I56303344","display_name":"Aselsan (Turkey)","ror":"https://ror.org/04knh8e66","country_code":"TR","type":"company","lineage":["https://openalex.org/I56303344"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"\u00c7a\u011fatay I\u015f\u0131l","raw_affiliation_strings":["Akıllı Veri Analitiği Araştırma Program Müdürlüğü, Aselsan Araştırma Merkezi, Ankara, Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Akıllı Veri Analitiği Araştırma Program Müdürlüğü, Aselsan Araştırma Merkezi, Ankara, Türkiye","institution_ids":["https://openalex.org/I56303344"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022226583","display_name":"Berkan Solmaz","orcid":"https://orcid.org/0000-0002-2252-1478"},"institutions":[{"id":"https://openalex.org/I56303344","display_name":"Aselsan (Turkey)","ror":"https://ror.org/04knh8e66","country_code":"TR","type":"company","lineage":["https://openalex.org/I56303344"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Berkan Solmaz","raw_affiliation_strings":["Akıllı Veri Analitiği Araştırma Program Müdürlüğü, Aselsan Araştırma Merkezi, Ankara, Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Akıllı Veri Analitiği Araştırma Program Müdürlüğü, Aselsan Araştırma Merkezi, Ankara, Türkiye","institution_ids":["https://openalex.org/I56303344"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062231547","display_name":"Aykut Ko\u00e7","orcid":"https://orcid.org/0000-0002-6348-2663"},"institutions":[{"id":"https://openalex.org/I56303344","display_name":"Aselsan (Turkey)","ror":"https://ror.org/04knh8e66","country_code":"TR","type":"company","lineage":["https://openalex.org/I56303344"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Aykut Ko\u00e7","raw_affiliation_strings":["Akıllı Veri Analitiği Araştırma Program Müdürlüğü, Aselsan Araştırma Merkezi, Ankara, Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Akıllı Veri Analitiği Araştırma Program Müdürlüğü, Aselsan Araştırma Merkezi, Ankara, Türkiye","institution_ids":["https://openalex.org/I56303344"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I56303344"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9998999834060669,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9998999834060669,"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/T11309","display_name":"Music and Audio Processing","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10862","display_name":"AI in cancer detection","score":0.9789999723434448,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.701442539691925},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6987317204475403},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6755973696708679},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6290598511695862},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.6081132292747498},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5331971049308777},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4894646406173706},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.48859530687332153},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4686262905597687},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4626518189907074},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4534067213535309},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4179993271827698},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40439489483833313},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.05794185400009155}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.701442539691925},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6987317204475403},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6755973696708679},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6290598511695862},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.6081132292747498},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5331971049308777},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4894646406173706},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.48859530687332153},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4686262905597687},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4626518189907074},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4534067213535309},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4179993271827698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40439489483833313},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.05794185400009155},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu.2018.8404227","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2018.8404227","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1959608418","https://openalex.org/W1963882359","https://openalex.org/W1965555277","https://openalex.org/W1975517671","https://openalex.org/W2100495367","https://openalex.org/W2153635508","https://openalex.org/W2163922914","https://openalex.org/W2187089797","https://openalex.org/W2316564661","https://openalex.org/W2598634450","https://openalex.org/W2964121744"],"related_works":["https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000","https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4281663961","https://openalex.org/W3208888551","https://openalex.org/W4313561566","https://openalex.org/W3208386644"],"abstract_inverted_index":{"Learning":[0],"low":[1],"dimensional":[2],"meaningful":[3],"representations":[4],"of":[5,25,61,70],"data":[6],"is":[7,21,76],"an":[8],"important":[9],"task":[10],"for":[11,18],"classification,":[12],"visualization":[13],"and":[14,45],"compression.":[15],"Using":[16],"autoencoders":[17,30,40,63,72],"representation":[19],"learning":[20],"a":[22,47],"successful":[23],"application":[24],"deep":[26],"learning.":[27],"Recently,":[28],"variational":[29,62,71],"have":[31,46],"also":[32],"been":[33],"developed.":[34],"These":[35],"are":[36,43],"more":[37],"advantageous":[38],"than":[39],"since":[41],"these":[42],"generative":[44],"compact":[48],"form":[49],"in":[50,64,78],"the":[51,58,65,68],"latent":[52,66],"space.":[53],"In":[54],"order":[55],"to":[56],"improve":[57],"clustering":[59],"performance":[60],"space,":[67],"use":[69],"with":[73],"triplet":[74],"loss":[75],"proposed":[77],"this":[79],"study.":[80]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}