{"id":"https://openalex.org/W2995174043","doi":"https://doi.org/10.1109/ritapp.2019.8932731","title":"Cross-Domain Knowledge Transfer for Incremental Deep Learning in Facial Expression Recognition","display_name":"Cross-Domain Knowledge Transfer for Incremental Deep Learning in Facial Expression Recognition","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W2995174043","doi":"https://doi.org/10.1109/ritapp.2019.8932731","mag":"2995174043"},"language":"en","primary_location":{"id":"doi:10.1109/ritapp.2019.8932731","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ritapp.2019.8932731","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 7th International Conference on Robot Intelligence Technology and Applications (RiTA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10072/389873","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090649922","display_name":"Nehemia Sugianto","orcid":"https://orcid.org/0000-0001-7342-3045"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Nehemia Sugianto","raw_affiliation_strings":["Department of Business Strategy and Innovation, Griffith University, Queensland, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Business Strategy and Innovation, Griffith University, Queensland, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053074581","display_name":"Dian Tjondronegoro","orcid":"https://orcid.org/0000-0001-7446-2839"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Dian Tjondronegoro","raw_affiliation_strings":["Department of Business Strategy and Innovation, Griffith University, Queensland, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Business Strategy and Innovation, Griffith University, Queensland, Australia","institution_ids":["https://openalex.org/I11701301"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5090649922"],"corresponding_institution_ids":["https://openalex.org/I11701301"],"apc_list":null,"apc_paid":null,"fwci":0.1919,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61374943,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"81","issue":null,"first_page":"205","last_page":"209"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9994000196456909,"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":0.9994000196456909,"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/T11448","display_name":"Face recognition and analysis","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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.996399998664856,"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/computer-science","display_name":"Computer science","score":0.8249533176422119},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7016457915306091},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6134568452835083},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5956429839134216},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5843191146850586},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5581139326095581},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.5506052374839783},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5153626799583435},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5106671452522278},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.4866548180580139},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4702160656452179},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4616381824016571},{"id":"https://openalex.org/keywords/humanoid-robot","display_name":"Humanoid robot","score":0.45344406366348267},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.44753479957580566},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.38550907373428345},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.086295485496521}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8249533176422119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7016457915306091},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6134568452835083},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5956429839134216},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5843191146850586},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5581139326095581},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.5506052374839783},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5153626799583435},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5106671452522278},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.4866548180580139},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4702160656452179},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4616381824016571},{"id":"https://openalex.org/C60692881","wikidata":"https://www.wikidata.org/wiki/Q584529","display_name":"Humanoid robot","level":3,"score":0.45344406366348267},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.44753479957580566},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.38550907373428345},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.086295485496521},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ritapp.2019.8932731","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ritapp.2019.8932731","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 7th International Conference on Robot Intelligence Technology and Applications (RiTA)","raw_type":"proceedings-article"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/389873","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/389873","pdf_url":"http://hdl.handle.net/10072/389873","source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"}],"best_oa_location":{"id":"pmh:oai:research-repository.griffith.edu.au:10072/389873","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/389873","pdf_url":"http://hdl.handle.net/10072/389873","source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2995174043.pdf"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1595126664","https://openalex.org/W2036868818","https://openalex.org/W2103943262","https://openalex.org/W2117539524","https://openalex.org/W2125127226","https://openalex.org/W2194775991","https://openalex.org/W2253728219","https://openalex.org/W2515770085","https://openalex.org/W2604474127","https://openalex.org/W2745497104","https://openalex.org/W2758375579","https://openalex.org/W2851948290","https://openalex.org/W2914933130","https://openalex.org/W2963839617","https://openalex.org/W2995813858","https://openalex.org/W4293659930","https://openalex.org/W6742835484","https://openalex.org/W6753127804"],"related_works":["https://openalex.org/W2745063183","https://openalex.org/W2129850190","https://openalex.org/W4256317079","https://openalex.org/W2295425790","https://openalex.org/W4389009354","https://openalex.org/W1974803039","https://openalex.org/W1991876829","https://openalex.org/W2088677124","https://openalex.org/W1589423663","https://openalex.org/W2642127892"],"abstract_inverted_index":{"For":[0],"robotics":[1],"and":[2,18,46,88,99,161],"AI":[3],"applications,":[4],"automatic":[5],"facial":[6,108],"expression":[7,109],"recognition":[8,110],"can":[9,169],"be":[10,60,126],"used":[11,82],"to":[12,32,41,59,84,144,152,174],"measure":[13],"user's":[14],"satisfaction":[15],"on":[16,62,95,115],"products":[17],"services":[19],"that":[20,159],"are":[21,29,112],"provided":[22],"through":[23],"the":[24,55,96,102,182],"human-computer":[25],"interactions.":[26],"Large-scale":[27],"datasets":[28,168],"essentially":[30],"required":[31],"construct":[33],"a":[34,80,116,130,140,171,177],"robust":[35],"deep":[36],"learning":[37,146],"model,":[38],"which":[39,123],"leads":[40],"increased":[42],"training":[43,56,90,119,163,175],"computation":[44,70],"cost":[45],"duration.":[47],"This":[48,137],"requirement":[49],"is":[50,57],"of":[51],"particular":[52],"issue":[53],"when":[54],"supposed":[58],"performed":[61],"an":[63],"ongoing":[64],"basis":[65],"in":[66,133],"devices":[67],"with":[68],"limited":[69],"capacity,":[71],"such":[72],"as":[73],"humanoid":[74],"robots.":[75],"Knowledge":[76],"transfer":[77,142],"has":[78],"become":[79],"commonly":[81],"technique":[83],"adapt":[85],"existing":[86,97],"models":[87,111],"speed-up":[89],"process":[91],"by":[92],"supporting":[93],"refinements":[94],"parameters":[98],"weights":[100],"for":[101,128],"target":[103,183],"task.":[104],"However,":[105],"most":[106],"state-of-the-art":[107],"still":[113],"based":[114],"single":[117,178],"stage":[118],"(train":[120],"at":[121],"once),":[122],"would":[124],"not":[125],"enough":[127],"achieving":[129],"satisfactory":[131],"performance":[132,173],"real":[134],"world":[135],"scenarios.":[136],"paper":[138],"proposes":[139],"knowledge":[141],"method":[143],"support":[145],"using":[147,164,176],"cross-domain":[148,167],"datasets,":[149],"from":[150,166,181],"generic":[151],"specific":[153],"domain.":[154,184],"The":[155],"experimental":[156],"results":[157],"demonstrate":[158],"shorter":[160],"incremental":[162],"smaller-gap-domain":[165],"achieve":[170],"comparable":[172],"large":[179],"dataset":[180]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
