{"id":"https://openalex.org/W4205551150","doi":"https://doi.org/10.1109/smc52423.2021.9658888","title":"Invariant Feature Extraction for CNN Classifier by using Gradient Reversal Layer","display_name":"Invariant Feature Extraction for CNN Classifier by using Gradient Reversal Layer","publication_year":2021,"publication_date":"2021-10-17","ids":{"openalex":"https://openalex.org/W4205551150","doi":"https://doi.org/10.1109/smc52423.2021.9658888"},"language":"en","primary_location":{"id":"doi:10.1109/smc52423.2021.9658888","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc52423.2021.9658888","pdf_url":null,"source":{"id":"https://openalex.org/S4363607761","display_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5086678336","display_name":"Michiaki Ueda","orcid":null},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Michiaki Ueda","raw_affiliation_strings":["Faculty of Graduate School of Advanced Science and Engineering, Hiroshima University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Graduate School of Advanced Science and Engineering, Hiroshima University","institution_ids":["https://openalex.org/I113306721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036393985","display_name":"Keijiro Kanda","orcid":null},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keijiro Kanda","raw_affiliation_strings":["Faculty of Graduate School of Advanced Science and Engineering, Hiroshima University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Graduate School of Advanced Science and Engineering, Hiroshima University","institution_ids":["https://openalex.org/I113306721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030040541","display_name":"Junichi Miyao","orcid":"https://orcid.org/0000-0001-8545-0630"},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Junichi Miyao","raw_affiliation_strings":["Faculty of Graduate School of Advanced Science and Engineering, Hiroshima University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Graduate School of Advanced Science and Engineering, Hiroshima University","institution_ids":["https://openalex.org/I113306721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108972118","display_name":"Shogo Miyamoto","orcid":null},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shogo Miyamoto","raw_affiliation_strings":["Faculty of Graduate School of Biomedical and Health Sciences, Hiroshima University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Graduate School of Biomedical and Health Sciences, Hiroshima University","institution_ids":["https://openalex.org/I113306721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077086654","display_name":"Yukiko Nakano","orcid":null},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yukiko Nakano","raw_affiliation_strings":["Faculty of Graduate School of Biomedical and Health Sciences, Hiroshima University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Graduate School of Biomedical and Health Sciences, Hiroshima University","institution_ids":["https://openalex.org/I113306721"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086456461","display_name":"Takio Kurita","orcid":"https://orcid.org/0000-0003-3982-6750"},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takio Kurita","raw_affiliation_strings":["Faculty of Graduate School of Advanced Science and Engineering, Hiroshima University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Graduate School of Advanced Science and Engineering, Hiroshima University","institution_ids":["https://openalex.org/I113306721"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I113306721"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"851","last_page":"856"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.996999979019165,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.996999979019165,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9945999979972839,"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/T10057","display_name":"Face and Expression Recognition","score":0.9919999837875366,"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":0.7701457142829895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7123812437057495},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6688466668128967},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6198936104774475},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6028995513916016},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.593239963054657},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.43060675263404846},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4251898229122162},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3506695628166199},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0984945297241211}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7701457142829895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7123812437057495},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6688466668128967},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6198936104774475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6028995513916016},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.593239963054657},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.43060675263404846},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4251898229122162},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3506695628166199},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0984945297241211},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc52423.2021.9658888","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc52423.2021.9658888","pdf_url":null,"source":{"id":"https://openalex.org/S4363607761","display_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W117943111","https://openalex.org/W1480376833","https://openalex.org/W1731081199","https://openalex.org/W1784100992","https://openalex.org/W1989426736","https://openalex.org/W2012945211","https://openalex.org/W2046336333","https://openalex.org/W2076434944","https://openalex.org/W2079439024","https://openalex.org/W2080645829","https://openalex.org/W2095976476","https://openalex.org/W2116350560","https://openalex.org/W2137291015","https://openalex.org/W2168792050","https://openalex.org/W2750384547","https://openalex.org/W2795155917","https://openalex.org/W2808376087","https://openalex.org/W2953127297","https://openalex.org/W2964656600","https://openalex.org/W2976670645","https://openalex.org/W3009323727","https://openalex.org/W3089211228","https://openalex.org/W6604815279","https://openalex.org/W6637618735","https://openalex.org/W6677088203","https://openalex.org/W6680112165","https://openalex.org/W6725448924","https://openalex.org/W6743688258","https://openalex.org/W6750109254"],"related_works":["https://openalex.org/W4389443772","https://openalex.org/W2548721895","https://openalex.org/W2373456246","https://openalex.org/W1926563137","https://openalex.org/W2013265273","https://openalex.org/W2982642565","https://openalex.org/W4238809000","https://openalex.org/W2786646446","https://openalex.org/W2113421559","https://openalex.org/W2985118265"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"has":[2],"been":[3],"successfully":[4],"applied":[5],"to":[6,30,45,75,100,112,125,142,155],"a":[7,12,65,69],"variety":[8],"of":[9,14,49,104,146,158],"tasks.":[10],"However,":[11],"lot":[13],"unnecessary":[15,34,81,117,134,152],"information":[16,35,82,88,119,170],"for":[17,56,89],"the":[18,23,37,47,50,53,77,86,90,102,105,121,127,130,138,144,156,159,168,172,178],"task":[19],"is":[20,28,43,111,124,141],"included":[21],"in":[22,36,52,148,171],"training":[24],"data":[25,55,150],"and":[26,83,120],"it":[27,42],"difficult":[29],"automatically":[31],"remove":[32],"such":[33],"trained":[38],"model.":[39],"For":[40],"example,":[41],"necessary":[44],"ignore":[46],"variations":[48,153],"patients":[51],"measured":[54],"medical":[57,149],"diagnosis.":[58],"To":[59],"address":[60],"this":[61,94],"problem,":[62],"we":[63,96,164],"propose":[64],"method":[66],"that":[67],"applies":[68],"module":[70],"called":[71],"Gradient":[72],"Reversal":[73],"Layer":[74],"train":[76],"model":[78],"by":[79],"removing":[80],"extracting":[84],"only":[85],"relevant":[87],"target":[91],"task.":[92],"In":[93,161],"study,":[95],"conducted":[97],"three":[98],"experiments":[99],"demonstrate":[101],"effectiveness":[103],"proposed":[106],"method.":[107],"The":[108],"first":[109],"one":[110,123,140],"classify":[113],"clothing":[114],"images":[115,132],"with":[116,133,151],"shift":[118],"second":[122],"identify":[126],"person":[128],"from":[129],"face":[131],"facial":[135],"expressions.":[136],"Finally,":[137],"third":[139],"estimate":[143],"presence":[145],"diseases":[147],"due":[154],"differences":[157],"patients.":[160],"all":[162],"experiments,":[163],"obtained":[165],"results":[166],"where":[167],"unwanted":[169],"features":[173],"was":[174],"reduced,":[175],"thereby":[176],"improving":[177],"desired":[179],"classification":[180],"performance.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}