{"id":"https://openalex.org/W4313045149","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892402","title":"Selective and Representative Sequence Feature Alignment for Domain Adaptive Detection Transformer","display_name":"Selective and Representative Sequence Feature Alignment for Domain Adaptive Detection Transformer","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4313045149","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892402"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892402","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892402","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5100619257","display_name":"Zhiyuan Yang","orcid":"https://orcid.org/0000-0002-2250-7959"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhi-Yuan Yang","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University,Suzhou,China,215006"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University,Suzhou,China,215006","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029104204","display_name":"Yi Ji","orcid":"https://orcid.org/0000-0001-6965-4158"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Ji","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University,Suzhou,China,215006"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University,Suzhou,China,215006","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100704240","display_name":"Ying Li","orcid":"https://orcid.org/0000-0003-2103-6646"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Li","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University,Suzhou,China,215006"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University,Suzhou,China,215006","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058448163","display_name":"Chunping Liu","orcid":"https://orcid.org/0009-0008-1495-5138"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun-Ping Liu","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University,Suzhou,China,215006"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University,Suzhou,China,215006","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100619257"],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":0.1039,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.33478776,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"17","issue":null,"first_page":"01","last_page":"08"},"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":0.9994000196456909,"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":0.9994000196456909,"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":0.9962000250816345,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.992900013923645,"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/computer-science","display_name":"Computer science","score":0.7695850133895874},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6814465522766113},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.6170426607131958},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6149963736534119},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5686073899269104},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5223199725151062},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3833509087562561},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.14612898230552673},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12263593077659607}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7695850133895874},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6814465522766113},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6170426607131958},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6149963736534119},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5686073899269104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5223199725151062},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3833509087562561},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.14612898230552673},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12263593077659607},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892402","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892402","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3398038842","display_name":null,"funder_award_id":"61972059","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":32,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1731081199","https://openalex.org/W2104094955","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2593768305","https://openalex.org/W2745461083","https://openalex.org/W2748021867","https://openalex.org/W2950800384","https://openalex.org/W2955889502","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963730616","https://openalex.org/W2964115968","https://openalex.org/W2968634921","https://openalex.org/W2979548969","https://openalex.org/W2982770724","https://openalex.org/W3034779842","https://openalex.org/W3034937575","https://openalex.org/W3035673985","https://openalex.org/W3092462694","https://openalex.org/W3096609285","https://openalex.org/W3106250896","https://openalex.org/W3107090469","https://openalex.org/W3110011650","https://openalex.org/W3186269967","https://openalex.org/W3189423081","https://openalex.org/W3206713300","https://openalex.org/W3213646008","https://openalex.org/W6637618735","https://openalex.org/W6714138976","https://openalex.org/W6760947256"],"related_works":["https://openalex.org/W4304700937","https://openalex.org/W2601157893","https://openalex.org/W2373006798","https://openalex.org/W2131735617","https://openalex.org/W2056912418","https://openalex.org/W2123759770","https://openalex.org/W2151520854","https://openalex.org/W2033213769","https://openalex.org/W4312376745","https://openalex.org/W2136016640"],"abstract_inverted_index":{"Recently,":[0],"several":[1],"studies":[2],"have":[3],"applied":[4],"the":[5,21,42,47,57,99,103,125,129],"Unsupervised":[6],"Domain":[7],"Adaptation":[8],"(UDA)":[9],"method":[10,54,156],"on":[11,29,56,150],"detection":[12,18,58,95],"transformers":[13],"to":[14,97,123],"improve":[15],"their":[16],"cross-domain":[17],"performance.":[19],"However,":[20],"majority":[22],"of":[23,93,102,128],"them":[24],"directly":[25],"apply":[26],"adversarial":[27],"alignment":[28,43,66,140],"expatiatory":[30],"token":[31,104],"sequences,":[32],"which":[33],"will":[34],"introduce":[35],"too":[36],"much":[37],"background":[38],"information":[39,127],"and":[40,62,80,146],"disturb":[41],"process.":[44],"To":[45],"tackle":[46],"problem,":[48],"we":[49],"propose":[50],"a":[51,144],"domain":[52,82],"adaption":[53],"focused":[55],"transformer":[59,94],"named":[60],"selective":[61],"representative":[63,126],"sequence":[64],"feature":[65,139],"(SR-SFA).":[67],"Specifically,":[68],"our":[69,155],"SR-SFA":[70],"contains":[71],"two":[72,151],"modules:":[73],"self-guided":[74],"weight":[75],"map":[76],"generation":[77,84],"module":[78,85,89,112],"(SWG)":[79],"classification-guided":[81],"query":[83],"(CQG).":[86],"The":[87,109],"SWG":[88],"takes":[90],"full":[91],"advantage":[92],"capability":[96],"locate":[98],"foreground":[100],"parts":[101],"sequences":[105],"for":[106,132],"local":[107,145],"alignment.":[108,135],"other":[110,162],"CQG":[111],"introduces":[113],"an":[114,120],"image-level":[115],"multi-label":[116],"classification":[117],"task":[118,122],"as":[119],"auxiliary":[121],"capture":[124],"whole":[130],"image":[131],"global":[133,147],"level":[134],"Therefore,":[136],"more":[137],"effective":[138],"is":[141],"performed":[142],"in":[143],"fashion.":[148],"Experiments":[149],"adaptation":[152],"scenarios":[153],"demonstrate":[154],"gets":[157],"better":[158],"performance":[159],"compared":[160],"with":[161],"approaches.":[163]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}