{"id":"https://openalex.org/W4392979749","doi":"https://doi.org/10.1109/tcss.2024.3367972","title":"Graph Convolutional Network for Adversarial Domain Generalization","display_name":"Graph Convolutional Network for Adversarial Domain Generalization","publication_year":2024,"publication_date":"2024-03-20","ids":{"openalex":"https://openalex.org/W4392979749","doi":"https://doi.org/10.1109/tcss.2024.3367972"},"language":"en","primary_location":{"id":"doi:10.1109/tcss.2024.3367972","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2024.3367972","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"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 Computational Social Systems","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/A5062448758","display_name":"Xiaoqing Zhang","orcid":"https://orcid.org/0009-0008-4906-1409"},"institutions":[{"id":"https://openalex.org/I4210115395","display_name":"Taiyuan Institute of Technology","ror":"https://ror.org/02d0fkx94","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115395"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoqing Zhang","raw_affiliation_strings":["Taiyuan Institute of Technology, Taiyuan, China"],"affiliations":[{"raw_affiliation_string":"Taiyuan Institute of Technology, Taiyuan, China","institution_ids":["https://openalex.org/I4210115395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101597275","display_name":"Hao Su","orcid":"https://orcid.org/0000-0002-6620-0801"},"institutions":[{"id":"https://openalex.org/I4210115395","display_name":"Taiyuan Institute of Technology","ror":"https://ror.org/02d0fkx94","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Su","raw_affiliation_strings":["Taiyuan Institute of Technology, Taiyuan, China"],"affiliations":[{"raw_affiliation_string":"Taiyuan Institute of Technology, Taiyuan, China","institution_ids":["https://openalex.org/I4210115395"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043852167","display_name":"Xuebin Liu","orcid":"https://orcid.org/0000-0003-1168-6565"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuebin Liu","raw_affiliation_strings":["Shanghai Zhongqiao Vocational and Technical University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Zhongqiao Vocational and Technical University, Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062448758"],"corresponding_institution_ids":["https://openalex.org/I4210115395"],"apc_list":null,"apc_paid":null,"fwci":0.7274,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.73154017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"12","issue":"4","first_page":"1785","last_page":"1793"},"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":0.9628999829292297,"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":0.9628999829292297,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9532999992370605,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9476000070571899,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6393462419509888},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5843874216079712},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5335970520973206},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48686379194259644},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.46025311946868896},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4334682822227478},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38416823744773865},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29202574491500854},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.2219071090221405}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6393462419509888},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5843874216079712},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5335970520973206},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48686379194259644},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.46025311946868896},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4334682822227478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38416823744773865},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29202574491500854},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.2219071090221405},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcss.2024.3367972","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2024.3367972","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"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 Computational Social Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W2115403315","https://openalex.org/W2116341502","https://openalex.org/W2593768305","https://openalex.org/W2627183927","https://openalex.org/W2763549966","https://openalex.org/W2765811365","https://openalex.org/W2798658180","https://openalex.org/W2894728917","https://openalex.org/W2958360136","https://openalex.org/W2963043696","https://openalex.org/W2963118547","https://openalex.org/W2981720610","https://openalex.org/W2998115938","https://openalex.org/W2998712190","https://openalex.org/W3038585207","https://openalex.org/W3095799614","https://openalex.org/W3109635165","https://openalex.org/W3109986233","https://openalex.org/W3153511633","https://openalex.org/W3169777530","https://openalex.org/W3175215201","https://openalex.org/W3183864931","https://openalex.org/W3207977952","https://openalex.org/W4213428547","https://openalex.org/W4220837741","https://openalex.org/W4285606900","https://openalex.org/W4304098271","https://openalex.org/W4307823382","https://openalex.org/W4312575870","https://openalex.org/W4315645290","https://openalex.org/W4387968528","https://openalex.org/W4387968704","https://openalex.org/W4388192945","https://openalex.org/W4390820252","https://openalex.org/W4391128392","https://openalex.org/W6629354409","https://openalex.org/W6720006811","https://openalex.org/W6748426227","https://openalex.org/W6754038005","https://openalex.org/W6780233385","https://openalex.org/W6780248173","https://openalex.org/W6785863445","https://openalex.org/W6789380839","https://openalex.org/W6796913975","https://openalex.org/W6802781638","https://openalex.org/W6803132187"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W4385627933","https://openalex.org/W2532801570","https://openalex.org/W2480127678","https://openalex.org/W2806270048","https://openalex.org/W4310605282"],"abstract_inverted_index":{"Domain":[0],"generalization":[1,72,83,122],"(DG)":[2],"aims":[3],"to":[4,47,89,95],"create":[5],"a":[6],"model":[7],"that":[8,36,116],"is":[9,16,50,92],"trained":[10],"across":[11,42],"multiple":[12],"source":[13],"domains":[14],"and":[15,40,104],"capable":[17],"of":[18,29],"performing":[19],"well":[20],"on":[21,112],"new,":[22],"previously":[23],"unseen":[24],"target":[25],"domains.":[26,43],"The":[27],"essence":[28],"this":[30,49],"task":[31],"lies":[32],"in":[33,99],"acquiring":[34],"features":[35],"are":[37],"both":[38],"discriminative":[39],"invariant":[41],"One":[44],"common":[45],"approach":[46],"achieve":[48],"through":[51],"adversarial":[52,58,81],"DG,":[53,100],"with":[54,66],"techniques":[55],"like":[56],"generative":[57],"networks":[59],"(GANs).":[60],"However,":[61],"these":[62],"methods":[63],"often":[64],"struggle":[65],"limited":[67],"intraclass":[68],"diversity,":[69],"hindering":[70],"their":[71],"capabilities.":[73],"To":[74],"address":[75],"this,":[76],"we":[77],"introduce":[78],"the":[79,93],"graph":[80,97],"domain":[82],"(GADG)":[84],"method.":[85],"This":[86],"novel":[87],"approach,":[88],"our":[90],"knowledge,":[91],"first":[94],"incorporate":[96],"information":[98],"effectively":[101],"learning":[102],"domain-invariant":[103],"semantic":[105],"representations.":[106],"Our":[107],"extensive":[108],"image":[109],"classification":[110],"tests":[111],"benchmark":[113],"datasets":[114],"show":[115],"GADG":[117],"not":[118],"only":[119],"achieves":[120],"robust":[121],"but":[123],"also":[124],"surpasses":[125],"existing":[126],"state-of-the-art":[127],"DG":[128],"methods.":[129]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
