{"id":"https://openalex.org/W4417438677","doi":"https://doi.org/10.1109/jiot.2025.3645096","title":"UAV Cross-Domain Detection in IoT-Enabled Environments via Class-Aware Correlation-Controlled Feature Learning","display_name":"UAV Cross-Domain Detection in IoT-Enabled Environments via Class-Aware Correlation-Controlled Feature Learning","publication_year":2025,"publication_date":"2025-12-17","ids":{"openalex":"https://openalex.org/W4417438677","doi":"https://doi.org/10.1109/jiot.2025.3645096"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2025.3645096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3645096","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","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":null,"display_name":"Guohao Feng","orcid":"https://orcid.org/0009-0009-2368-0815"},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guohao Feng","raw_affiliation_strings":["Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0009-2368-0815","affiliations":[{"raw_affiliation_string":"Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]},{"raw_affiliation_string":"Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Pengda Wang","orcid":"https://orcid.org/0009-0009-2958-455X"},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengda Wang","raw_affiliation_strings":["Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0009-2958-455X","affiliations":[{"raw_affiliation_string":"Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]},{"raw_affiliation_string":"Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073958113","display_name":"Yiran Xie","orcid":"https://orcid.org/0009-0000-1444-9827"},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiran Xie","raw_affiliation_strings":["Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0000-1444-9827","affiliations":[{"raw_affiliation_string":"Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]},{"raw_affiliation_string":"Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenzhong Shen","orcid":"https://orcid.org/0009-0004-0471-4972"},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzhong Shen","raw_affiliation_strings":["Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0004-0471-4972","affiliations":[{"raw_affiliation_string":"Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]},{"raw_affiliation_string":"Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078232413","display_name":"Jundong Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jundong Zeng","raw_affiliation_strings":["Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]},{"raw_affiliation_string":"Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102988843","display_name":"Jie Shao","orcid":"https://orcid.org/0009-0007-5070-1349"},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Shao","raw_affiliation_strings":["Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0007-5070-1349","affiliations":[{"raw_affiliation_string":"Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]},{"raw_affiliation_string":"Department of Electronics and information engineering, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19293127,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"5","first_page":"9177","last_page":"9191"},"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":0.8773000240325928,"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":0.8773000240325928,"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":0.038100000470876694,"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/T11448","display_name":"Face recognition and analysis","score":0.007899999618530273,"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/adaptability","display_name":"Adaptability","score":0.5618000030517578},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5252000093460083},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.521399974822998},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.48820000886917114},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48669999837875366},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4487000107765198},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.40869998931884766},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4083999991416931},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3991999924182892},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.39100000262260437}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8363000154495239},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6258999705314636},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5618000030517578},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5252000093460083},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.521399974822998},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.48820000886917114},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48669999837875366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45649999380111694},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4487000107765198},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.40869998931884766},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4083999991416931},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3991999924182892},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.39100000262260437},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3885999917984009},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.382099986076355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37950000166893005},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.35440000891685486},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.34630000591278076},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.32820001244544983},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.30239999294281006},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.296999990940094},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28299999237060547},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.2766999900341034},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.26820001006126404},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.26499998569488525},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2025.3645096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3645096","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-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/W639708223","https://openalex.org/W1638081485","https://openalex.org/W2031342017","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2565639579","https://openalex.org/W2808646376","https://openalex.org/W2958360136","https://openalex.org/W2962777203","https://openalex.org/W2963037989","https://openalex.org/W2995484963","https://openalex.org/W3038585207","https://openalex.org/W3043995050","https://openalex.org/W3093105758","https://openalex.org/W3096609285","https://openalex.org/W3180303049","https://openalex.org/W4312740566","https://openalex.org/W4316673310","https://openalex.org/W4319990398","https://openalex.org/W4386066146","https://openalex.org/W4387623981","https://openalex.org/W4389104778","https://openalex.org/W4390488653","https://openalex.org/W4393148824","https://openalex.org/W4393178495","https://openalex.org/W4393185921","https://openalex.org/W4395115932","https://openalex.org/W4402727489","https://openalex.org/W4405106491"],"related_works":[],"abstract_inverted_index":{"Unmanned":[0],"Aerial":[1],"Vehicle":[2],"(UAV)":[3],"cross-domain":[4],"detection":[5],"aims":[6],"to":[7,12,126,149,178],"enhance":[8],"the":[9,38,88,92,184,195,202],"model\u2019s":[10],"adaptability":[11],"diverse":[13],"environments,":[14],"thereby":[15,109,135],"mitigating":[16],"performance":[17,186],"degradation":[18],"caused":[19],"by":[20],"domain":[21,31,107],"shifts.":[22],"Although":[23],"significant":[24,51],"progress":[25],"has":[26],"been":[27],"made":[28],"in":[29,47],"UAV":[30,48],"generalization":[32,112],"detection,":[33],"distribution":[34],"shifts,":[35,108],"coupled":[36],"with":[37],"high":[39],"visual":[40],"similarity":[41],"between":[42,94,152],"foreground":[43],"and":[44,67,71,96,132,154,170,204],"background":[45],"regions":[46],"imagery,":[49],"remain":[50],"challenges.":[52],"Traditional":[53],"domain-invariant":[54],"feature":[55,64,83],"decoupling":[56],"methods":[57],"suffer":[58],"from":[59,87],"problems":[60],"such":[61],"as":[62,174],"breaking":[63],"semantic":[65],"integrity":[66],"introducing":[68],"complex":[69],"computational":[70,164],"architectural":[72],"demands.":[73],"To":[74,114],"address":[75],"these":[76],"issues,":[77],"we":[78],"propose":[79],"a":[80,117,141,175],"class-aware":[81,119,142],"correlationcontrolled":[82],"learning":[84],"(CFL)":[85],"method":[86,159,189],"perspective":[89],"of":[90,187],"analyzing":[91],"correlation":[93,143,151],"class-relevant":[95,102,131,153],"class-irrelevant":[97,133,155],"features.":[98,139,156],"It":[99],"focuses":[100],"on":[101,190,200],"features":[103],"for":[104],"prediction":[105],"under":[106],"achieving":[110],"better":[111],"performance.":[113],"this":[115],"end,":[116],"weight-based":[118],"kernel":[120],"selection":[121],"strategy":[122,177],"(WCKS)":[123],"is":[124,147],"introduced":[125],"categorize":[127],"convolutional":[128],"kernels":[129],"into":[130],"sets,":[134],"extracting":[136],"their":[137],"corresponding":[138],"Furthermore,":[140],"loss":[144],"(CC":[145],"loss)":[146],"designed":[148],"penalize":[150],"Our":[157],"proposed":[158],"does":[160],"not":[161],"introduce":[162],"extra":[163],"or":[165],"model":[166],"complexity":[167],"during":[168],"deployment,":[169],"it":[171],"can":[172],"serve":[173],"regularization":[176],"various":[179],"tasks.":[180],"Experimental":[181],"results":[182,198],"demonstrate":[183],"state-of-the-art":[185],"our":[188],"benchmark":[191],"datasets,":[192],"notably":[193],"surpassing":[194],"best":[196],"reported":[197],"(UAV-OD)":[199],"both":[201],"UAVDT":[203],"VisDrone2019-VID":[205],"datasets.":[206],"The":[207],"code":[208],"will":[209],"be":[210],"released":[211],"at":[212],"https://github.com/Jackie239/CFL.":[213]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-12-17T00:00:00"}