{"id":"https://openalex.org/W4362710651","doi":"https://doi.org/10.1145/3582649.3582671","title":"Smile Recognition Based on Comprehensive Dataset Construction and Bayesian Neural Architecture Search","display_name":"Smile Recognition Based on Comprehensive Dataset Construction and Bayesian Neural Architecture Search","publication_year":2023,"publication_date":"2023-01-06","ids":{"openalex":"https://openalex.org/W4362710651","doi":"https://doi.org/10.1145/3582649.3582671"},"language":"en","primary_location":{"id":"doi:10.1145/3582649.3582671","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3582649.3582671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 6th International Conference on Image and Graphics Processing","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/A5050710252","display_name":"Junjie Huang","orcid":"https://orcid.org/0000-0001-8950-2602"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Huang","raw_affiliation_strings":["School of Mathematical Sciences, Ocean University of China, China"],"raw_orcid":"https://orcid.org/0000-0001-8950-2602","affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Ocean University of China, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010062798","display_name":"Yangfan Deng","orcid":"https://orcid.org/0000-0002-0676-2896"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangfan Deng","raw_affiliation_strings":["School of Mathematical Sciences, Ocean University of China, China"],"raw_orcid":"https://orcid.org/0000-0002-0676-2896","affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Ocean University of China, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021937568","display_name":"Qinghua Guo","orcid":"https://orcid.org/0000-0001-6776-0766"},"institutions":[{"id":"https://openalex.org/I106994412","display_name":"Sinopec (China)","ror":"https://ror.org/0161q6d74","country_code":"CN","type":"company","lineage":["https://openalex.org/I106994412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Guo","raw_affiliation_strings":["Sinopec Geophysical Research Institute Co.Ltd, China"],"raw_orcid":"https://orcid.org/0000-0001-6776-0766","affiliations":[{"raw_affiliation_string":"Sinopec Geophysical Research Institute Co.Ltd, China","institution_ids":["https://openalex.org/I106994412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001234679","display_name":"Yizhou Xu","orcid":"https://orcid.org/0000-0001-9435-5934"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yizhou Xu","raw_affiliation_strings":["School of Mathematical Sciences, Ocean University of China, China"],"raw_orcid":"https://orcid.org/0000-0001-9435-5934","affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Ocean University of China, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qingtao Pan","orcid":"https://orcid.org/0000-0001-9648-8618"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingtao Pan","raw_affiliation_strings":["School of Mathematical Sciences, Ocean University of China, China"],"raw_orcid":"https://orcid.org/0000-0001-9648-8618","affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Ocean University of China, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101990819","display_name":"Yong Zhao","orcid":"https://orcid.org/0000-0002-5617-0004"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Zhao","raw_affiliation_strings":["School of Mathematical Sciences, Ocean University of China, China"],"raw_orcid":"https://orcid.org/0000-0002-5617-0004","affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Ocean University of China, China","institution_ids":["https://openalex.org/I59028903"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02494738,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"31","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9945999979972839,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9945999979972839,"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/T11448","display_name":"Face recognition and analysis","score":0.986299991607666,"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":0.9855999946594238,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8208714723587036},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7783090472221375},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.6615334749221802},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6509907245635986},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.631008505821228},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5687103271484375},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5285854339599609},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.48905691504478455},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4617282450199127},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4580610394477844},{"id":"https://openalex.org/keywords/variable-order-bayesian-network","display_name":"Variable-order Bayesian network","score":0.4569031298160553},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.4520152509212494},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40506142377853394},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32723525166511536},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.25472724437713623},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08305403590202332}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8208714723587036},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7783090472221375},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.6615334749221802},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6509907245635986},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.631008505821228},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5687103271484375},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5285854339599609},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.48905691504478455},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4617282450199127},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4580610394477844},{"id":"https://openalex.org/C71983512","wikidata":"https://www.wikidata.org/wiki/Q7915687","display_name":"Variable-order Bayesian network","level":4,"score":0.4569031298160553},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.4520152509212494},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40506142377853394},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32723525166511536},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.25472724437713623},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08305403590202332},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3582649.3582671","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3582649.3582671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 6th International Conference on Image and Graphics Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1458181269","display_name":null,"funder_award_id":"202061046","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G1834238422","display_name":null,"funder_award_id":"ZR2018MF006","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"}],"funders":[{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W212125716","https://openalex.org/W2041616772","https://openalex.org/W2125127226","https://openalex.org/W2133180260","https://openalex.org/W2157653492","https://openalex.org/W2168893862","https://openalex.org/W2169931729","https://openalex.org/W2413582689","https://openalex.org/W2483634599","https://openalex.org/W2550222318","https://openalex.org/W2612866255","https://openalex.org/W2745497104","https://openalex.org/W2780562800","https://openalex.org/W2835246884","https://openalex.org/W2912500072","https://openalex.org/W2951003875","https://openalex.org/W4211047281","https://openalex.org/W4236965008","https://openalex.org/W4319068731","https://openalex.org/W6658226468","https://openalex.org/W6675736572","https://openalex.org/W6679879939","https://openalex.org/W6697219101"],"related_works":["https://openalex.org/W2383034311","https://openalex.org/W2592745513","https://openalex.org/W643788828","https://openalex.org/W2391701421","https://openalex.org/W201565394","https://openalex.org/W4309448762","https://openalex.org/W2353852789","https://openalex.org/W2985695769","https://openalex.org/W1700460858","https://openalex.org/W4211221765"],"abstract_inverted_index":{"Smile":[0],"recognition":[1],"is":[2,132],"a":[3,15,47],"very":[4],"important":[5],"topic":[6],"in":[7,71,79,117],"image":[8],"processing":[9],"and":[10,13,66,82,101,112],"deep":[11],"learning,":[12],"has":[14],"certain":[16],"practical":[17],"significance.":[18],"At":[19],"present,":[20],"existing":[21],"datasets":[22],"tend":[23],"to":[24,34,93],"have":[25],"simple":[26],"backgrounds":[27],"or":[28,63,68],"imbalanced":[29],"ethnicities.":[30],"And":[31,84],"researchers":[32],"need":[33],"build":[35,95],"convolutional":[36,98],"neural":[37,89],"networks":[38],"empirically.":[39],"To":[40],"address":[41],"these":[42],"problems,":[43],"we":[44,86],"first":[45],"construct":[46],"comprehensive":[48],"dataset":[49,75],"which":[50],"contains":[51],"10,392":[52],"images":[53],"of":[54,124,129,136],"four":[55],"major":[56],"races":[57],"(i.e.,":[58],"White,":[59],"Asian,":[60],"American":[61],"Native":[62],"Pacific":[64],"Islander,":[65],"Black":[67],"African":[69],"American)":[70],"complex":[72],"backgrounds.":[73],"Our":[74],"exhibits":[76],"larger":[77],"variations":[78],"background,":[80],"illumination,":[81],"ethnicity.":[83],"then,":[85],"apply":[87],"Bayesian":[88,115],"architecture":[90,100,107],"search":[91],"algorithm":[92],"automatically":[94],"the":[96,118,122,127,137],"optimal":[97],"network":[99,106,131],"perform":[102],"model":[103],"training.":[104],"The":[105],"can":[108],"be":[109],"repeatedly":[110],"searched":[111],"optimized":[113],"through":[114],"optimizer":[116],"specified":[119],"time.":[120],"Through":[121],"comparisons":[123],"experimental":[125],"data,":[126],"performance":[128],"our":[130],"better":[133],"than":[134],"those":[135],"classical":[138],"networks.":[139]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
