{"id":"https://openalex.org/W2995728175","doi":"https://doi.org/10.1145/3368926.3369707","title":"Building Face Recognition System with Triplet-based Stacked Variational Denoising Autoencoder","display_name":"Building Face Recognition System with Triplet-based Stacked Variational Denoising Autoencoder","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2995728175","doi":"https://doi.org/10.1145/3368926.3369707","mag":"2995728175"},"language":"en","primary_location":{"id":"doi:10.1145/3368926.3369707","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3368926.3369707","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth International Symposium on Information and Communication Technology  - SoICT 2019","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/A5069344139","display_name":"Xuan Tuan Le","orcid":"https://orcid.org/0000-0002-4192-810X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xuan Tuan Le","raw_affiliation_strings":["People's Security Academy, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"People's Security Academy, Hanoi, Vietnam","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5069344139"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14979873,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"106","last_page":"110"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","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/T11448","display_name":"Face recognition and analysis","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/T10057","display_name":"Face and Expression Recognition","score":0.9986000061035156,"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":0.9965000152587891,"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/autoencoder","display_name":"Autoencoder","score":0.8219135999679565},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7933158874511719},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.73725426197052},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6885387897491455},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6400443315505981},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6196014285087585},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5971970558166504},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5721648931503296},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5080366134643555},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4967549443244934},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.46827104687690735},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4640815258026123},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.41302600502967834},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3354722559452057},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2442580759525299},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1586398184299469}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8219135999679565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7933158874511719},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.73725426197052},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6885387897491455},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6400443315505981},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6196014285087585},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5971970558166504},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5721648931503296},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5080366134643555},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4967549443244934},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.46827104687690735},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4640815258026123},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.41302600502967834},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3354722559452057},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2442580759525299},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1586398184299469},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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":1,"locations":[{"id":"doi:10.1145/3368926.3369707","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3368926.3369707","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth International Symposium on Information and Communication Technology  - SoICT 2019","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":19,"referenced_works":["https://openalex.org/W1546200464","https://openalex.org/W1834627138","https://openalex.org/W1975517671","https://openalex.org/W2095705004","https://openalex.org/W2096733369","https://openalex.org/W2097117768","https://openalex.org/W2100495367","https://openalex.org/W2137857332","https://openalex.org/W2145287260","https://openalex.org/W2157364932","https://openalex.org/W2163605009","https://openalex.org/W2164598857","https://openalex.org/W2166694921","https://openalex.org/W2194775991","https://openalex.org/W2417429787","https://openalex.org/W2528578439","https://openalex.org/W2770994131","https://openalex.org/W2787121704","https://openalex.org/W3099206234"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2145836866","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W3037110488"],"abstract_inverted_index":{"Face":[0],"recognition":[1,16],"is":[2,27,58,103],"a":[3,14,53,62,78],"fundamental":[4],"and":[5,42,68,132],"critical":[6],"topic":[7],"in":[8,96,105],"computer":[9],"vision.":[10],"In":[11,49],"this":[12],"work,":[13],"face":[15,36,108],"system":[17,102,121],"based":[18,135],"on":[19],"stacked":[20,54],"variational":[21,55],"denoising":[22,56],"autoencoders":[23,95],"with":[24,45,74],"triplet":[25,79],"loss":[26,80],"proposed":[28,51,101,120],"to":[29,35,60,125],"overcome":[30],"some":[31,106],"existing":[32],"challenges":[33],"regard":[34],"variations":[37],"including":[38,110],"poses,":[39],"illumination,":[40],"expression":[41],"low":[43],"resolution":[44],"less":[46],"training":[47],"data.":[48,72],"our":[50],"system,":[52],"autoencoder":[57],"used":[59],"build":[61],"deep":[63,127],"architecture":[64],"for":[65],"extracting":[66],"salient":[67],"latent":[69],"features":[70],"from":[71],"Together":[73],"that,":[75],"by":[76],"using":[77],"function,":[81],"we":[82],"can":[83],"preserve":[84],"categorical":[85],"similarity":[86],"between":[87],"faces,":[88],"then":[89],"improve":[90],"the":[91,94,97,119],"performance":[92],"of":[93],"clustering":[98],"task.":[99],"The":[100],"evaluated":[104],"benchmark":[107],"datasets":[109],"ORL,":[111],"Yale,":[112],"Youtube":[113],"Faces.":[114],"Preliminary":[115],"results":[116,124],"demonstrate":[117],"that":[118],"yields":[122],"comparable":[123],"other":[126],"convolutional":[128],"neural":[129],"networks":[130],"(CNN)":[131],"none-deep":[133],"CNN":[134],"methods.":[136]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
