{"id":"https://openalex.org/W4379646519","doi":"https://doi.org/10.2298/csis221228034j","title":"Heterogenous-view occluded expression data recognition based on cycle-consistent adversarial network and K-SVD dictionary learning under intelligent cooperative robot environment","display_name":"Heterogenous-view occluded expression data recognition based on cycle-consistent adversarial network and K-SVD dictionary learning under intelligent cooperative robot environment","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4379646519","doi":"https://doi.org/10.2298/csis221228034j"},"language":"en","primary_location":{"id":"doi:10.2298/csis221228034j","is_oa":true,"landing_page_url":"https://doi.org/10.2298/csis221228034j","pdf_url":"http://www.doiserbia.nb.rs/ft.aspx?id=1820-02142300034J","source":{"id":"https://openalex.org/S206939107","display_name":"Computer Science and Information Systems","issn_l":"1820-0214","issn":["1820-0214","2406-1018"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310321031","host_organization_name":"ComSIS Consortium","host_organization_lineage":["https://openalex.org/P4310321031"],"host_organization_lineage_names":["ComSIS Consortium"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Science and Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"http://www.doiserbia.nb.rs/ft.aspx?id=1820-02142300034J","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037178287","display_name":"Yu Jiang","orcid":"https://orcid.org/0000-0001-9025-3375"},"institutions":[{"id":"https://openalex.org/I32399674","display_name":"Shenyang Normal University","ror":"https://ror.org/05cdfgm80","country_code":"CN","type":"education","lineage":["https://openalex.org/I32399674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Jiang","raw_affiliation_strings":["College of Fine Art and Design, Shenyang Normal University Shenyang, China","College of Fine Art and Design, Shenyang Normal University Shenyang, 110034 China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Fine Art and Design, Shenyang Normal University Shenyang, China","institution_ids":["https://openalex.org/I32399674"]},{"raw_affiliation_string":"College of Fine Art and Design, Shenyang Normal University Shenyang, 110034 China","institution_ids":["https://openalex.org/I32399674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041576447","display_name":"Shoulin Yin","orcid":"https://orcid.org/0000-0002-5367-1372"},"institutions":[{"id":"https://openalex.org/I32399674","display_name":"Shenyang Normal University","ror":"https://ror.org/05cdfgm80","country_code":"CN","type":"education","lineage":["https://openalex.org/I32399674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shoulin Yin","raw_affiliation_strings":["Software College, Shenyang Normal University Shenyang, China","Software College, Shenyang Normal University Shenyang, 110034 China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Software College, Shenyang Normal University Shenyang, China","institution_ids":["https://openalex.org/I32399674"]},{"raw_affiliation_string":"Software College, Shenyang Normal University Shenyang, 110034 China","institution_ids":["https://openalex.org/I32399674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I32399674"],"apc_list":null,"apc_paid":null,"fwci":1.5954,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.85543158,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"20","issue":"4","first_page":"1869","last_page":"1883"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9896000027656555,"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":0.9896000027656555,"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/T14254","display_name":"Digital Media and Visual Art","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.923799991607666,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7817713618278503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.675284206867218},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.6474277973175049},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.581591784954071},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.45354050397872925},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.4380784332752228},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.419463574886322},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.41421395540237427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7817713618278503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.675284206867218},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.6474277973175049},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.581591784954071},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.45354050397872925},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.4380784332752228},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.419463574886322},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.41421395540237427},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2298/csis221228034j","is_oa":true,"landing_page_url":"https://doi.org/10.2298/csis221228034j","pdf_url":"http://www.doiserbia.nb.rs/ft.aspx?id=1820-02142300034J","source":{"id":"https://openalex.org/S206939107","display_name":"Computer Science and Information Systems","issn_l":"1820-0214","issn":["1820-0214","2406-1018"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310321031","host_organization_name":"ComSIS Consortium","host_organization_lineage":["https://openalex.org/P4310321031"],"host_organization_lineage_names":["ComSIS Consortium"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Science and Information Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.2298/csis221228034j","is_oa":true,"landing_page_url":"https://doi.org/10.2298/csis221228034j","pdf_url":"http://www.doiserbia.nb.rs/ft.aspx?id=1820-02142300034J","source":{"id":"https://openalex.org/S206939107","display_name":"Computer Science and Information Systems","issn_l":"1820-0214","issn":["1820-0214","2406-1018"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310321031","host_organization_name":"ComSIS Consortium","host_organization_lineage":["https://openalex.org/P4310321031"],"host_organization_lineage_names":["ComSIS Consortium"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Science and Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6100000143051147,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4379646519.pdf"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2089480358","https://openalex.org/W2133513216","https://openalex.org/W2163398148","https://openalex.org/W2738672149","https://openalex.org/W2885976210","https://openalex.org/W2916199694","https://openalex.org/W2962716958","https://openalex.org/W2963720440","https://openalex.org/W2963856926","https://openalex.org/W2964347837","https://openalex.org/W3003720578","https://openalex.org/W3088420159","https://openalex.org/W3094151137","https://openalex.org/W3096831136","https://openalex.org/W3097711533","https://openalex.org/W3118530108","https://openalex.org/W3133735015","https://openalex.org/W3135044423","https://openalex.org/W3165352316","https://openalex.org/W3173573364","https://openalex.org/W3179103990","https://openalex.org/W3215476595","https://openalex.org/W4226093122","https://openalex.org/W4296143831","https://openalex.org/W4310536495"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W2387995142","https://openalex.org/W4380714744","https://openalex.org/W4319453655","https://openalex.org/W2089959425","https://openalex.org/W2057775761","https://openalex.org/W1608433645","https://openalex.org/W2964074194"],"abstract_inverted_index":{"In":[0,29,40,59],"space":[1],"art":[2],"design,":[3],"the":[4,13,37,41,51,63,93,97,103,109,114,125,133,142,146,157,160,165,170,174,181,202,214,221,233,237,241,252,265,271],"recognition":[5,67,85,269],"of":[6,9,15,43,53,65,116,132,180,205,216,240,267,273],"expression":[7,24,66,84,111,182,198,218],"is":[8,18,32,47,138,210,244],"great":[10],"help":[11],"to":[12,21,35,49,61,123,140,155,213,220],"understanding":[14],"art.":[16],"It":[17],"very":[19,33],"difficult":[20,48],"obtain":[22],"occlusion":[23],"data":[25,118],"from":[26,173],"robot":[27,90],"environment.":[28,91],"particular,":[30],"it":[31,46,209],"challenging":[34],"recognize":[36],"occluded":[38,54,83],"expression.":[39],"case":[42,272],"facial":[44,268,274],"occlusion,":[45],"extract":[50],"features":[52,196,199],"expressions":[55],"by":[56,200],"traditional":[57,253],"methods.":[58],"order":[60,122],"reduce":[62],"dependence":[64],"on":[68,159,227],"individuals,":[69],"this":[70,261],"paper":[71],"proposes":[72],"a":[73,135,177],"cycle-consistent":[74],"adversarial":[75,100],"network":[76,101,161,256],"and":[77,128,149,163,197,230,247,258],"K-SVD":[78],"dictionary":[79],"learning":[80],"method":[81,95],"for":[82],"in":[86,121,270],"education":[87],"management":[88],"under":[89],"Firstly,":[92],"new":[94,242],"uses":[96],"cyclic-consistent":[98],"generation":[99,130],"as":[102],"skeleton":[104],"model,":[105],"which":[106],"can":[107,185],"generate":[108],"un-occluded":[110],"image":[112,129,166,179,190],"without":[113],"need":[115],"paired":[117],"sets.":[119],"Meanwhile,":[120],"improve":[124,164],"discriminant":[126,143],"ability":[127,131],"network,":[134],"multi-scale":[136],"discriminator":[137],"used":[139,154],"construct":[141],"network.":[144],"Then,":[145],"least":[147],"squares":[148],"cyclic":[150],"sensing":[151],"loss":[152],"are":[153,192],"strengthen":[156],"constraints":[158],"model":[162,243,262],"quality.":[167],"By":[168],"subtracting":[169],"error":[171],"matrix":[172],"test":[175],"sample,":[176],"clear":[178,189],"classification":[183],"stage":[184],"be":[186],"recovered.":[187],"The":[188],"samples":[191],"decomposed":[193],"into":[194],"identity":[195],"using":[201],"collaborative":[203],"representation":[204],"two":[206],"dictionaries.":[207],"Finally,":[208],"classified":[211],"according":[212],"contribution":[215],"each":[217],"feature":[219],"joint":[222],"sparse":[223],"representation.":[224],"Experiments":[225],"conducted":[226],"CK+,":[228],"RAF-DB":[229],"SFEW":[231],"datasets,":[232],"results":[234],"show":[235],"that":[236],"average":[238],"accuracy":[239,266],"98.44%,":[245],"87.12%":[246],"62.17%,":[248],"respectively.":[249],"Compared":[250],"with":[251],"convolutional":[254],"neural":[255],"models":[257],"advanced":[259],"methods,":[260],"effectively":[263],"improves":[264],"occlusion.":[275]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
