{"id":"https://openalex.org/W4400070538","doi":"https://doi.org/10.1109/tii.2024.3414489","title":"Hierarchical Co-Consistency Quantization and Information Refining Binary Network for Facial Expression Recognition in Human\u2013Robot Interaction","display_name":"Hierarchical Co-Consistency Quantization and Information Refining Binary Network for Facial Expression Recognition in Human\u2013Robot Interaction","publication_year":2024,"publication_date":"2024-06-27","ids":{"openalex":"https://openalex.org/W4400070538","doi":"https://doi.org/10.1109/tii.2024.3414489"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2024.3414489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3414489","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-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/A5012120468","display_name":"Cheng-Shan Jiang","orcid":"https://orcid.org/0000-0002-8524-8165"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng-Shan Jiang","raw_affiliation_strings":["School of Automation, China University of Geosciences, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-8524-8165","affiliations":[{"raw_affiliation_string":"School of Automation, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101455965","display_name":"Zhentao Liu","orcid":"https://orcid.org/0000-0003-4100-9557"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen-Tao Liu","raw_affiliation_strings":["School of Automation, China University of Geosciences, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-4100-9557","affiliations":[{"raw_affiliation_string":"School of Automation, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101916568","display_name":"Jinhua She","orcid":"https://orcid.org/0000-0003-3165-5045"},"institutions":[{"id":"https://openalex.org/I148798404","display_name":"Tokyo University of Technology","ror":"https://ror.org/021a26605","country_code":"JP","type":"education","lineage":["https://openalex.org/I148798404"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jinhua She","raw_affiliation_strings":["School of Engineering, Tokyo University of Technology, Hachioji, Japan"],"raw_orcid":"https://orcid.org/0000-0003-3165-5045","affiliations":[{"raw_affiliation_string":"School of Engineering, Tokyo University of Technology, Hachioji, Japan","institution_ids":["https://openalex.org/I148798404"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.1166,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.97965484,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"20","issue":"10","first_page":"12178","last_page":"12188"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9204000234603882,"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":0.9204000234603882,"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/T10057","display_name":"Face and Expression Recognition","score":0.9160000085830688,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.5931633114814758},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.577484667301178},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.544631838798523},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.4730602502822876},{"id":"https://openalex.org/keywords/human\u2013robot-interaction","display_name":"Human\u2013robot interaction","score":0.4657474458217621},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.4617901146411896},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4431920647621155},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43490374088287354},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.42652615904808044},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.40267789363861084},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35702353715896606},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.199477881193161}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5931633114814758},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.577484667301178},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.544631838798523},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.4730602502822876},{"id":"https://openalex.org/C145460709","wikidata":"https://www.wikidata.org/wiki/Q859951","display_name":"Human\u2013robot interaction","level":3,"score":0.4657474458217621},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.4617901146411896},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4431920647621155},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43490374088287354},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.42652615904808044},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.40267789363861084},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35702353715896606},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.199477881193161},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2024.3414489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3414489","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4300000071525574,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G6079930777","display_name":null,"funder_award_id":"61273102","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7050647769","display_name":null,"funder_award_id":"61403422","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8708917460","display_name":null,"funder_award_id":"61976197","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2012945211","https://openalex.org/W2060681345","https://openalex.org/W2083021723","https://openalex.org/W2150283722","https://openalex.org/W2300242332","https://openalex.org/W2754021867","https://openalex.org/W2889978276","https://openalex.org/W2896555122","https://openalex.org/W2950956522","https://openalex.org/W2970987838","https://openalex.org/W2982344224","https://openalex.org/W2995813858","https://openalex.org/W3003720578","https://openalex.org/W3008515144","https://openalex.org/W3041607159","https://openalex.org/W3100408030","https://openalex.org/W3166284037","https://openalex.org/W3179103990","https://openalex.org/W3194949249","https://openalex.org/W3205895757","https://openalex.org/W3209798173","https://openalex.org/W3216427062","https://openalex.org/W4210729356","https://openalex.org/W4291128471","https://openalex.org/W4312806248","https://openalex.org/W4317033482","https://openalex.org/W4319996317","https://openalex.org/W4320489184","https://openalex.org/W4362496449","https://openalex.org/W4372260294","https://openalex.org/W4376278471","https://openalex.org/W4385245566","https://openalex.org/W4386161521","https://openalex.org/W4389169982","https://openalex.org/W6693397755","https://openalex.org/W6767164110"],"related_works":["https://openalex.org/W1603736412","https://openalex.org/W2392243736","https://openalex.org/W86652014","https://openalex.org/W4304185162","https://openalex.org/W2061685118","https://openalex.org/W3006282800","https://openalex.org/W2642127892","https://openalex.org/W2722112567","https://openalex.org/W2775620487","https://openalex.org/W3122170352"],"abstract_inverted_index":{"Facial":[0],"expression":[1,98],"recognition":[2],"(FER)":[3],"has":[4,37],"become":[5],"a":[6,61,96],"trending":[7],"research":[8],"topic":[9],"in":[10,31,43,52,155],"human\u2013robot":[11],"interaction":[12],"(HRI).":[13],"However,":[14],"the":[15,45,48,53,117,135,141,150],"conventional":[16],"CNN-based":[17],"FER":[18,54,75],"methods":[19],"encounter":[20],"challenges":[21],"related":[22],"to":[23,40,90],"robustness":[24],"and":[25,66,84,107,123,131],"computational":[26,46],"efficiency,":[27],"limiting":[28],"their":[29],"applicability":[30],"HRI":[32,156],"contexts.":[33],"Although":[34],"weight":[35],"binarization":[36],"been":[38],"proved":[39],"be":[41],"effective":[42],"reducing":[44],"complexity,":[47],"loss":[49,126],"of":[50,111,140,152],"accuracy":[51],"task":[55],"is":[56,72,102],"significant.":[57],"In":[58],"this":[59],"article,":[60],"hierarchical":[62],"co-consistency":[63],"quantization":[64],"(HCQ)":[65],"information":[67,100,110],"refining":[68],"binary":[69,132,142],"network":[70],"(IRBN)":[71],"proposed":[73,103],"for":[74,104],"during":[76],"HRI.":[77],"The":[78,144],"IRBN":[79,118],"incorporates":[80],"one-shot":[81],"aggregation":[82],"(OSA)":[83],"convolution":[85],"with":[86],"edge":[87],"difference":[88],"mask":[89],"preserve":[91],"low-level":[92],"texture":[93],"features,":[94],"while":[95],"facial":[97],"semantic":[99,109],"refiner":[101],"filtering":[105],"irrelevant":[106],"ambiguous":[108],"high-level":[112],"abstract":[113],"features.":[114],"HCQ":[115],"optimizes":[116],"through":[119],"progressive":[120],"sign":[121],"function":[122],"layer-by-layer":[124],"feature":[125,137],"derived":[127],"from":[128],"both":[129],"full-precision":[130],"networks,":[133],"maintaining":[134],"strong":[136],"extraction":[138],"capability":[139],"network.":[143],"preliminary":[145],"application":[146],"experimental":[147],"result":[148],"demonstrates":[149],"feasibility":[151],"our":[153],"method":[154],"scenarios.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":20}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}
