{"id":"https://openalex.org/W7124844570","doi":"https://doi.org/10.1109/access.2026.3656395","title":"MSF-YOLOv11n: A Multi-Scale Feature Fusion-Based Efficient Detector for Small and Occluded Object Detection in Complex Traffic Scenes","display_name":"MSF-YOLOv11n: A Multi-Scale Feature Fusion-Based Efficient Detector for Small and Occluded Object Detection in Complex Traffic Scenes","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7124844570","doi":"https://doi.org/10.1109/access.2026.3656395"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3656395","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3656395","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3656395","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Sheng Xu","orcid":"https://orcid.org/0009-0001-9687-5113"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Xu","raw_affiliation_strings":["College of Electronics and Information, Zhengzhou University of Light Industry, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0009-0001-9687-5113","affiliations":[{"raw_affiliation_string":"College of Electronics and Information, Zhengzhou University of Light Industry, Zhengzhou, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhongpei Sun","orcid":"https://orcid.org/0009-0007-6359-0748"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongpei Sun","raw_affiliation_strings":["College of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-6359-0748","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123384793","display_name":"Hong Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Xu","raw_affiliation_strings":["College of Electronics and Information, Zhengzhou University of Light Industry, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0009-0003-9843-4105","affiliations":[{"raw_affiliation_string":"College of Electronics and Information, Zhengzhou University of Light Industry, Zhengzhou, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123446263","display_name":"Wei Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Huang","raw_affiliation_strings":["College of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123382470","display_name":"Qiqiang Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiqiang Chen","raw_affiliation_strings":["College of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0009-0005-5965-7853","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123395159","display_name":"Hongjie He","orcid":null},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongjie He","raw_affiliation_strings":["College of Electronics and Information, Zhengzhou University of Light Industry, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronics and Information, Zhengzhou University of Light Industry, Zhengzhou, China","institution_ids":["https://openalex.org/I23171815"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I23171815"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06751168,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"81515","last_page":"81534"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9731000065803528,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9731000065803528,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.003700000001117587,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.003100000089034438,"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/upsampling","display_name":"Upsampling","score":0.8238999843597412},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5715000033378601},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5679000020027161},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.5375999808311462},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5264000296592712},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.4643999934196472},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4580000042915344},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.40310001373291016},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3864000141620636},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.3628999888896942}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8309000134468079},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.8238999843597412},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6646000146865845},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5885000228881836},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5715000033378601},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5679000020027161},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.5375999808311462},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5264000296592712},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.4643999934196472},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4580000042915344},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3864000141620636},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.3628999888896942},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.3626999855041504},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3598000109195709},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.319599986076355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C141297171","wikidata":"https://www.wikidata.org/wiki/Q1143237","display_name":"Octree","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.30720001459121704},{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C173642442","wikidata":"https://www.wikidata.org/wiki/Q1253346","display_name":"Decimation","level":3,"score":0.3012000024318695},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3656395","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3656395","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:518ee1f9f5aa4c049328fcedd9efafba","is_oa":true,"landing_page_url":"https://doaj.org/article/518ee1f9f5aa4c049328fcedd9efafba","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 81515-81534 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3656395","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3656395","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4280482232570648},{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.4088318347930908}],"awards":[{"id":"https://openalex.org/G3009469526","display_name":null,"funder_award_id":"62201512","funder_id":"https://openalex.org/F4320333688","funder_display_name":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China"},{"id":"https://openalex.org/G3307327978","display_name":null,"funder_award_id":"252102210001","funder_id":"https://openalex.org/F4320336593","funder_display_name":"Henan Provincial Science and Technology Research Project"},{"id":"https://openalex.org/G4293798924","display_name":null,"funder_award_id":"252102210131","funder_id":"https://openalex.org/F4320336593","funder_display_name":"Henan Provincial Science and Technology Research Project"},{"id":"https://openalex.org/G4721944735","display_name":null,"funder_award_id":"62201512","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4745367496","display_name":null,"funder_award_id":"25102210001","funder_id":"https://openalex.org/F4320336593","funder_display_name":"Henan Provincial Science and Technology Research Project"},{"id":"https://openalex.org/G8269281101","display_name":null,"funder_award_id":"252102211065","funder_id":"https://openalex.org/F4320336593","funder_display_name":"Henan Provincial Science and Technology Research Project"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320333688","display_name":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China","ror":null},{"id":"https://openalex.org/F4320336593","display_name":"Henan Provincial Science and Technology Research Project","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Detecting":[0],"small":[1],"and":[2,24,75,95,100,124,132,140,153,159,164,179,199],"occluded":[3],"objects":[4],"in":[5,20,107,162,166],"complex":[6],"traffic":[7,203],"scenes":[8],"remains":[9],"a":[10,40,97,125,172,194],"major":[11],"challenge":[12],"for":[13,201],"intelligent":[14],"transportation":[15],"systems,":[16],"including":[17],"the":[18,51,66,82,108,112],"difficulty":[19],"balancing":[21],"high":[22],"accuracy":[23,198],"low":[25],"computational":[26,173],"cost.":[27],"To":[28],"address":[29],"these":[30],"challenges,":[31],"this":[32],"paper":[33],"proposes":[34],"an":[35,180],"innovative":[36,47],"MSF-YOLOv11n":[37,148,192],"model.":[38],"With":[39],"modular":[41],"architecture":[42],"design,":[43],"we":[44],"propose":[45],"three":[46],"technical":[48],"frameworks.":[49],"First,":[50],"Adaptive":[52],"Attention-Enhanced":[53],"Wavelet":[54],"Module":[55,86,118],"(AAEWM)":[56],"performs":[57],"multi-scale":[58,137],"wavelet":[59],"decomposition":[60],"combined":[61],"with":[62,92,146,171],"attention-guided":[63],"reconstruction,":[64],"enabling":[65],"model":[67],"to":[68],"capture":[69],"structural":[70],"information":[71],"such":[72],"as":[73],"edges":[74],"textures":[76],"while":[77],"suppressing":[78],"noise":[79],"interference.":[80],"Second,":[81],"Feature-Enhanced":[83],"Attention":[84,94,117],"Upsampling":[85],"(FEAUM)":[87],"integrates":[88],"lightweight":[89],"Ghost":[90],"convolution":[91,101],"Shuffle":[93],"employs":[96,120],"hybrid":[98],"interpolation":[99],"strategy,":[102],"which":[103],"preserves":[104],"fine-grained":[105],"details":[106],"upsampling":[109],"process.":[110],"Third,":[111],"Multi-Scale":[113],"Fusion":[114],"Lightweight":[115],"Triple":[116],"(MFTAM)":[119],"depthwise":[121],"separable":[122],"convolutions":[123],"triple":[126],"attention":[127],"mechanism":[128],"across":[129],"channel,":[130],"spatial":[131],"positional":[133],"dimensions,":[134],"effectively":[135],"enhancing":[136],"feature":[138],"interaction":[139],"improving":[141],"small-object":[142],"localization":[143],"accuracy.":[144],"Compared":[145],"YOLOv11n,":[147],"improves":[149],"mAP50-95":[150,163],"by":[151,155],"3.8%":[152],"mAP50":[154,167],"3.7%":[156],"on":[157,168,186],"UA-DETRAC,":[158],"gains":[160],"3.6%":[161],"3.9%":[165],"DAIR-V2X,":[169],"all":[170],"cost":[174],"of":[175,183,197],"only":[176],"6.5":[177],"GFLOPs":[178],"inference":[181],"speed":[182],"100":[184],"FPS":[185],"UA-DETRAC.":[187],"These":[188],"results":[189],"demonstrate":[190],"that":[191],"achieves":[193],"strong":[195],"balance":[196],"efficiency":[200],"real-world":[202],"perception.":[204]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2026-01-21T00:00:00"}
