{"id":"https://openalex.org/W7124905274","doi":"https://doi.org/10.1007/s11227-025-08186-7","title":"MSEF-YOLO11s: a multi-scale extraction and fusion network for small target detection in drone imagery","display_name":"MSEF-YOLO11s: a multi-scale extraction and fusion network for small target detection in drone imagery","publication_year":2026,"publication_date":"2026-01-20","ids":{"openalex":"https://openalex.org/W7124905274","doi":"https://doi.org/10.1007/s11227-025-08186-7"},"language":"en","primary_location":{"id":"doi:10.1007/s11227-025-08186-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11227-025-08186-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11227-025-08186-7.pdf","source":{"id":"https://openalex.org/S32326811","display_name":"The Journal of Supercomputing","issn_l":"0920-8542","issn":["0920-8542","1573-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of Supercomputing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11227-025-08186-7.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100323900","display_name":"Kai Zhang","orcid":"https://orcid.org/0000-0001-7902-0570"},"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":"Kai Zhang","raw_affiliation_strings":["Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365992","display_name":"Pengcheng Zhang","orcid":"https://orcid.org/0000-0003-3560-1167"},"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":"Pengcheng Zhang","raw_affiliation_strings":["Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China","institution_ids":["https://openalex.org/I23632641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101745850","display_name":"Farhan Ullah","orcid":"https://orcid.org/0000-0003-2422-575X"},"institutions":[{"id":"https://openalex.org/I138564716","display_name":"Prince Mohammad bin Fahd University","ror":"https://ror.org/03d64na34","country_code":"SA","type":"education","lineage":["https://openalex.org/I138564716"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Farhan Ullah","raw_affiliation_strings":["Cybersecurity Center, Prince Mohammad Bin Fahd University, 31952, Khobar, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Cybersecurity Center, Prince Mohammad Bin Fahd University, 31952, Khobar, Saudi Arabia","institution_ids":["https://openalex.org/I138564716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123030714","display_name":"Yue Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153668","display_name":"Wenzhou-Kean University","ror":"https://ror.org/05609xa16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153668"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yue Zhao","raw_affiliation_strings":["Department of Computer Science, College of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, Zhejiang, China","institution_ids":["https://openalex.org/I4210153668"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5123030714"],"corresponding_institution_ids":["https://openalex.org/I4210153668"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17518759,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"82","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5418000221252441,"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":0.5418000221252441,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.040800001472234726,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.03280000016093254,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.673799991607666},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6269999742507935},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5406000018119812},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.5317000150680542},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5135999917984009},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4814000129699707},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.45899999141693115},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44269999861717224},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4397999942302704}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9208999872207642},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.673799991607666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6392999887466431},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6269999742507935},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5406000018119812},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.5317000150680542},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5135999917984009},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4814000129699707},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47620001435279846},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.45899999141693115},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44269999861717224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4397999942302704},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4343000054359436},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42559999227523804},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.41670000553131104},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4074000120162964},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.39160001277923584},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.38190001249313354},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.3709999918937683},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.36880001425743103},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11227-025-08186-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11227-025-08186-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11227-025-08186-7.pdf","source":{"id":"https://openalex.org/S32326811","display_name":"The Journal of Supercomputing","issn_l":"0920-8542","issn":["0920-8542","1573-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of Supercomputing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11227-025-08186-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11227-025-08186-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11227-025-08186-7.pdf","source":{"id":"https://openalex.org/S32326811","display_name":"The Journal of Supercomputing","issn_l":"0920-8542","issn":["0920-8542","1573-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of Supercomputing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1611947856","display_name":null,"funder_award_id":"62372285","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","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":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W7124905274.pdf"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2102605133","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2964775615","https://openalex.org/W2995484963","https://openalex.org/W3009396058","https://openalex.org/W3034971973","https://openalex.org/W3035459165","https://openalex.org/W3210997334","https://openalex.org/W4250482878","https://openalex.org/W4291805279","https://openalex.org/W4312470530","https://openalex.org/W4327652243","https://openalex.org/W4376878836","https://openalex.org/W4385760871","https://openalex.org/W4386047745","https://openalex.org/W4386076325","https://openalex.org/W4386076539","https://openalex.org/W4386914050","https://openalex.org/W4387125416","https://openalex.org/W4387541834","https://openalex.org/W4391092744","https://openalex.org/W4391241798","https://openalex.org/W4391307079","https://openalex.org/W4391992749","https://openalex.org/W4396728056","https://openalex.org/W4401548585","https://openalex.org/W4401767441","https://openalex.org/W4402727675","https://openalex.org/W4402754006","https://openalex.org/W4402761423","https://openalex.org/W4402968335","https://openalex.org/W4404605649","https://openalex.org/W4404672078","https://openalex.org/W4405303628","https://openalex.org/W4408145528","https://openalex.org/W4409565071","https://openalex.org/W4413868834"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Small":[1],"object":[2,125],"detection":[3,32,101,126],"in":[4,57,73,149,160],"unmanned":[5],"aerial":[6,9],"vehicle":[7],"(UAV)":[8],"imagery":[10],"faces":[11],"substantial":[12],"challenges":[13],"due":[14],"to":[15,64,139,172],"small":[16,61,124],"target":[17],"scales,":[18],"complex":[19],"backgrounds,":[20],"noise":[21],"interference,":[22],"and":[23,31,53,69],"so":[24],"on.":[25],"To":[26],"enhance":[27],"multi-scale":[28,45,55,79],"feature":[29,67,71],"representation":[30],"efficiency,":[33],"this":[34],"paper":[35],"proposes":[36],"MSEF-YOLO11s.":[37],"Specifically,":[38,137],"we":[39,76],"first":[40],"design":[41],"a":[42,78,97,122],"lightweight":[43,98],"partial":[44],"(LPMS)":[46],"module,":[47],"which":[48,87],"effectively":[49],"aggregates":[50],"cross-scale":[51],"information":[52],"enhances":[54],"representations":[56],"the":[58,74,105,114,131,134,140,152,165,175],"backbone":[59],"for":[60,93],"objects.":[62],"Secondly,":[63],"dynamically":[65],"adjust":[66],"weights":[68],"mitigate":[70],"conflicts":[72],"neck,":[75],"devise":[77],"boundary-semantic":[80],"alignment":[81],"(MS-BSA)":[82],"based":[83],"on":[84,151,164],"adaptive":[85],"attention,":[86],"can":[88],"further":[89],"avoid":[90],"computational":[91],"redundancy":[92],"sufficient":[94],"fusion.":[95],"Finally,":[96],"shared":[99,110],"detail":[100],"head":[102,107],"(LSDDH)":[103],"replaces":[104],"decoupled":[106],"structure":[108],"with":[109,120,156],"convolutional":[111],"layers,":[112],"resolving":[113],"issue":[115],"of":[116,133,147],"parameter":[117],"explosion":[118],"associated":[119],"adding":[121],"dedicated":[123],"head.":[127],"Experimental":[128],"results":[129],"demonstrate":[130],"effectiveness":[132],"proposed":[135],"model.":[136],"compared":[138],"baseline":[141],"YOLO11s,":[142],"MSEF-YOLO11s":[143],"achieves":[144],"an":[145],"improvement":[146],"6.6%":[148],"mAP50":[150,163],"VisDrone2019":[153],"test":[154,167],"set,":[155],"only":[157],"4.4M":[158],"increase":[159],"parameters.":[161],"Furthermore,":[162],"TinyPerson":[166],"set":[168],"increases":[169],"from":[170],"22.8%":[171],"28.1%,":[173],"confirming":[174],"model\u2019s":[176],"strong":[177],"generalization":[178],"capability.":[179]},"counts_by_year":[],"updated_date":"2026-03-22T08:09:32.410652","created_date":"2026-01-21T00:00:00"}
