{"id":"https://openalex.org/W2902376486","doi":"https://doi.org/10.1109/icpr.2018.8545782","title":"Diversified Dual Domain-Adversarial Neural Networks","display_name":"Diversified Dual Domain-Adversarial Neural Networks","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902376486","doi":"https://doi.org/10.1109/icpr.2018.8545782","mag":"2902376486"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545782","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545782","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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/A5007282525","display_name":"Yuchun Fang","orcid":"https://orcid.org/0000-0002-7085-8876"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuchun Fang","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057318551","display_name":"Qiulong Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiulong Yuan","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084565580","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0002-1658-0236"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028016065","display_name":"Zhaoxiang Zhang","orcid":"https://orcid.org/0000-0003-2648-3875"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoxiang Zhang","raw_affiliation_strings":["University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"615","last_page":"620"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993000030517578,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9908000230789185,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8338809609413147},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.7349311113357544},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6796246767044067},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6324635148048401},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5885900855064392},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5146104097366333},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5139333605766296},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5055065155029297},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4880298674106598},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.44280827045440674},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42371347546577454},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4229661226272583},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4180121123790741},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3200884461402893}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8338809609413147},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.7349311113357544},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6796246767044067},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6324635148048401},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5885900855064392},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5146104097366333},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5139333605766296},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5055065155029297},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4880298674106598},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.44280827045440674},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42371347546577454},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4229661226272583},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4180121123790741},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3200884461402893},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8545782","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545782","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W16455933","https://openalex.org/W1490600648","https://openalex.org/W1565327149","https://openalex.org/W1577269164","https://openalex.org/W1722318740","https://openalex.org/W1731081199","https://openalex.org/W1861492603","https://openalex.org/W1882958252","https://openalex.org/W1892837366","https://openalex.org/W2067713319","https://openalex.org/W2095705004","https://openalex.org/W2099471712","https://openalex.org/W2104068492","https://openalex.org/W2104094955","https://openalex.org/W2104657103","https://openalex.org/W2105523772","https://openalex.org/W2108069432","https://openalex.org/W2110158442","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2125389028","https://openalex.org/W2128053425","https://openalex.org/W2149466042","https://openalex.org/W2159291411","https://openalex.org/W2163605009","https://openalex.org/W2173520492","https://openalex.org/W2186639548","https://openalex.org/W2521669777","https://openalex.org/W2552465644","https://openalex.org/W2567101557","https://openalex.org/W2605135824","https://openalex.org/W2605287558","https://openalex.org/W2618530766","https://openalex.org/W2768183993","https://openalex.org/W2776460497","https://openalex.org/W2953127297","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W2963275094","https://openalex.org/W2963684088","https://openalex.org/W2963709863","https://openalex.org/W2963826681","https://openalex.org/W2964201867","https://openalex.org/W2998115938","https://openalex.org/W3037567775","https://openalex.org/W4285719527","https://openalex.org/W4295521014","https://openalex.org/W4320013936","https://openalex.org/W6633949838","https://openalex.org/W6634441602","https://openalex.org/W6637542466","https://openalex.org/W6637618735","https://openalex.org/W6639102338","https://openalex.org/W6674330103","https://openalex.org/W6675865240","https://openalex.org/W6675930903","https://openalex.org/W6678815747","https://openalex.org/W6681637710","https://openalex.org/W6683633756","https://openalex.org/W6684191040","https://openalex.org/W6685352114","https://openalex.org/W6685415078","https://openalex.org/W6686604231"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W4380714744","https://openalex.org/W2387995142","https://openalex.org/W4319453655","https://openalex.org/W2089959425","https://openalex.org/W2964074194","https://openalex.org/W2057775761","https://openalex.org/W2995777218"],"abstract_inverted_index":{"The":[0,122,171],"application":[1],"cost":[2,29],"machine":[3],"learning":[4],"methods":[5],"often":[6,46],"rely":[7],"on":[8,163],"the":[9,19,89,96,100,117,135,140],"availability":[10],"of":[11,21,91,166,183],"large-scale":[12],"data":[13,35],"collection":[14],"and":[15,36,150],"annotation,":[16],"especially":[17],"in":[18],"cases":[20],"cross-domain":[22],"learning.":[23,93],"One":[24],"way":[25],"to":[26,33,54,63,98,128,133],"circumvent":[27],"this":[28,75],"is":[30,61],"constructing":[31],"models":[32,42,132,146,186],"synthesize":[34],"provide":[37],"automatic":[38],"annotation.":[39],"Although":[40],"these":[41,65,154],"are":[43],"attractive,":[44],"they":[45,69],"can":[47,70,108,124,177],"not":[48],"be":[49,71,125],"generalized":[50],"from":[51,103],"synthetic":[52],"images":[53],"real-world":[55],"images.":[56],"Therefore,":[57],"domain":[58,82,167,180],"adaptive":[59,83,168,181],"algorithm":[60],"needed":[62],"improve":[64,134],"models,":[66],"so":[67,151],"that":[68,174],"applied":[72],"successfully.":[73],"In":[74],"paper,":[76],"we":[77,159],"propose":[78],"a":[79],"novel":[80],"unsupervised":[81],"framework":[84,123],"codenamed":[85],"D-DANN":[86,141,155],"inspired":[87],"by":[88,116],"theory":[90],"adversarial":[92],"We":[94,107,138],"apply":[95],"discriminator":[97],"diverse":[99],"features":[101],"extracted":[102],"dual":[104,119],"branch":[105],"CNN.":[106],"obtain":[109],"more":[110],"sufficient":[111],"shared":[112],"representation":[113,136],"across":[114],"domains":[115],"proposed":[118],"feature":[120],"extractors.":[121],"easily":[126],"adapt":[127],"most":[129],"popular":[130,144],"CNN":[131,145,185],"power.":[137],"implement":[139],"with":[142],"several":[143,164],"including":[147],"LeNet,":[148],"AlexNet":[149],"on.":[152],"Using":[153],"enhanced":[156],"neural":[157],"networks,":[158],"conduct":[160],"extensive":[161],"experiments":[162],"pairs":[165],"validation":[169],"datasets.":[170],"results":[172],"show":[173],"our":[175],"approach":[176],"efficiently":[178],"enhance":[179],"capability":[182],"general":[184],"for":[187],"unlabeled":[188],"data.":[189]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}