{"id":"https://openalex.org/W7126120145","doi":"https://doi.org/10.3390/e28020150","title":"Cross-Dataset Facial Micro-Expression Recognition with Regularization Learning and Action Unit-Guided Data Augmentation","display_name":"Cross-Dataset Facial Micro-Expression Recognition with Regularization Learning and Action Unit-Guided Data Augmentation","publication_year":2026,"publication_date":"2026-01-29","ids":{"openalex":"https://openalex.org/W7126120145","doi":"https://doi.org/10.3390/e28020150","pmid":"https://pubmed.ncbi.nlm.nih.gov/41751653"},"language":"en","primary_location":{"id":"doi:10.3390/e28020150","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28020150","pdf_url":null,"source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/e28020150","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101053596","display_name":"Jin Zhou","orcid":"https://orcid.org/0000-0002-1534-2279"},"institutions":[{"id":"https://openalex.org/I182722699","display_name":"Shenzhen Polytechnic University","ror":"https://ror.org/00d2w9g53","country_code":"CN","type":"education","lineage":["https://openalex.org/I182722699"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ju Zhou","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China","Tech X Academy, Shenzhen Polytechnic University, Shenzhen 518055, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Tech X Academy, Shenzhen Polytechnic University, Shenzhen 518055, China","institution_ids":["https://openalex.org/I182722699"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100446462","display_name":"Xinyu Liu","orcid":"https://orcid.org/0009-0006-6086-9551"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Liu","raw_affiliation_strings":["School of Computer Science and Artificial Intelligence, Guangdong University of Education, Guangzhou 510303, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Artificial Intelligence, Guangdong University of Education, Guangzhou 510303, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lin Wang","orcid":"https://orcid.org/0000-0002-9111-2723"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]},{"id":"https://openalex.org/I4210153682","display_name":"Intelligent Health (United Kingdom)","ror":"https://ror.org/0576zak10","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210153682"]}],"countries":["CN","GB"],"is_corresponding":false,"raw_author_name":"Lin Wang","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China","Shenzhen Lower Limb Intelligent Rehabilitation Engineering Research Center, Shenzhen 518055, China"],"raw_orcid":"https://orcid.org/0000-0002-9111-2723","affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Shenzhen Lower Limb Intelligent Rehabilitation Engineering Research Center, Shenzhen 518055, China","institution_ids":["https://openalex.org/I4210153682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100669345","display_name":"Tao Wang","orcid":"https://orcid.org/0000-0001-9002-2630"},"institutions":[{"id":"https://openalex.org/I182722699","display_name":"Shenzhen Polytechnic University","ror":"https://ror.org/00d2w9g53","country_code":"CN","type":"education","lineage":["https://openalex.org/I182722699"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Wang","raw_affiliation_strings":["Tech X Academy, Shenzhen Polytechnic University, Shenzhen 518055, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tech X Academy, Shenzhen Polytechnic University, Shenzhen 518055, China","institution_ids":["https://openalex.org/I182722699"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113365558","display_name":"Haolin Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133785","display_name":"Rehab-Robotics (China)","ror":"https://ror.org/040kksw48","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210133785"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haolin Xia","raw_affiliation_strings":["Hong Kong Center for Construction Robotics, Hong Kong 999077, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong Center for Construction Robotics, Hong Kong 999077, China","institution_ids":["https://openalex.org/I4210133785"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101053596"],"corresponding_institution_ids":["https://openalex.org/I182722699","https://openalex.org/I19820366","https://openalex.org/I4210145761"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13907955,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":"2","first_page":"150","last_page":"150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.0020000000949949026,"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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.0015999999595806003,"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/regularization","display_name":"Regularization (linguistics)","score":0.7260000109672546},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7020999789237976},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5806000232696533},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5199000239372253},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49300000071525574},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4652999937534332},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.40849998593330383},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.388700008392334}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7534000277519226},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7260000109672546},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7020999789237976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6301000118255615},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5806000232696533},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5199000239372253},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5012999773025513},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49300000071525574},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.388700008392334},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3840000033378601},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.3702999949455261},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.31540000438690186},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.30300000309944153},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.2937999963760376},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e28020150","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28020150","pdf_url":null,"source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:41751653","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41751653","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:2218b35435654d619c2041b45f76f5f9","is_oa":false,"landing_page_url":"https://doaj.org/article/2218b35435654d619c2041b45f76f5f9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 28, Iss 2, p 150 (2026)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12939661","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12939661/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e28020150","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28020150","pdf_url":null,"source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7201692841","display_name":null,"funder_award_id":"62573402","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,65,69,94,108,147,156,159],"growing":[2],"development":[3],"of":[4,68,96,135,158],"facial":[5,20],"micro-expression":[6,21,38,124,152],"recognition":[7,22,39,183],"technology,":[8],"its":[9],"practical":[10],"application":[11],"value":[12],"has":[13],"attracted":[14],"increasing":[15],"attention.":[16],"In":[17],"real-world":[18],"scenarios,":[19],"typically":[23],"involves":[24],"cross-dataset":[25,37,182],"evaluation,":[26],"where":[27],"training":[28,43,58,74],"and":[29,44,60,169],"testing":[30],"samples":[31],"come":[32],"from":[33],"different":[34,73],"datasets.":[35],"Specifically,":[36],"employs":[40],"multi-dataset":[41],"composite":[42],"unseen":[45],"single-dataset":[46],"testing.":[47],"This":[48,126],"setup":[49],"introduces":[50],"two":[51],"major":[52],"challenges:":[53],"inconsistent":[54],"feature":[55],"distributions":[56],"across":[57,72,88],"sets":[59],"data":[61,109],"imbalance.":[62],"To":[63,106,154],"address":[64],"distribution":[66],"discrepancy":[67],"same":[70],"category":[71],"datasets,":[75],"we":[76,112],"propose":[77,113],"a":[78],"plug-and-play":[79],"batch":[80],"regularization":[81],"learning":[82,95],"module":[83],"that":[84,175],"constrains":[85],"weight":[86],"discrepancies":[87],"datasets":[89],"through":[90],"information-theoretic":[91],"regularization,":[92],"facilitating":[93],"domain-invariant":[97],"representations":[98],"while":[99],"preventing":[100],"overfitting":[101],"to":[102,131,145,185],"specific":[103],"source":[104],"domains.":[105],"mitigate":[107],"imbalance":[110],"issue,":[111],"an":[114],"Action":[115],"Unit":[116],"(AU)-guided":[117],"generative":[118],"adversarial":[119],"network":[120],"(GAN)":[121],"for":[122,138],"synthesizing":[123],"samples.":[125,153],"approach":[127,177],"uses":[128],"K-means":[129],"clustering":[130],"obtain":[132],"cluster":[133],"centers":[134],"AU":[136],"intensities":[137],"each":[139],"category,":[140],"which":[141],"are":[142,164],"then":[143],"used":[144],"guide":[146],"GAN":[148],"in":[149,181],"generating":[150],"balanced":[151],"validate":[155],"effectiveness":[157],"proposed":[160],"methods,":[161],"extensive":[162],"experiments":[163],"conducted":[165],"on":[166],"CNN,":[167],"ResNet,":[168],"PoolFormer":[170],"architectures.":[171],"The":[172],"results":[173],"demonstrate":[174],"our":[176],"achieves":[178],"superior":[179],"performance":[180],"compared":[184],"state-of-the-art":[186],"methods.":[187]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-01-30T00:00:00"}