{"id":"https://openalex.org/W7123358325","doi":"https://doi.org/10.1109/access.2026.3653122","title":"YOLOv11-HNU: Enhanced Unmanned Aerial Vehicle Target Detection Based on Improved YOLOv11","display_name":"YOLOv11-HNU: Enhanced Unmanned Aerial Vehicle Target Detection Based on Improved YOLOv11","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7123358325","doi":"https://doi.org/10.1109/access.2026.3653122"},"language":null,"primary_location":{"id":"doi:10.1109/access.2026.3653122","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653122","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.2026.3653122","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122853528","display_name":"Zhipeng Xue","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhipeng Xue","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi’an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0009-0002-6681-1343","affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi’an, Shaanxi, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122875026","display_name":"Lingyun Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingyun Kong","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi’an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0001-7248-3900","affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi’an, Shaanxi, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122846749","display_name":"Haiyang Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I63371133","display_name":"Chongqing Jiaotong University","ror":"https://ror.org/01t001k65","country_code":"CN","type":"education","lineage":["https://openalex.org/I63371133"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyang Wu","raw_affiliation_strings":["School of Traffic Transportation, Chongqing Jiaotong University, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0009-2122-7435","affiliations":[{"raw_affiliation_string":"School of Traffic Transportation, Chongqing Jiaotong University, Chongqing, China","institution_ids":["https://openalex.org/I63371133"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5122853528"],"corresponding_institution_ids":["https://openalex.org/I4210162994"],"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":0.06572181,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"9660","last_page":"9673"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.8188999891281128,"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":0.8188999891281128,"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/T11133","display_name":"UAV Applications and Optimization","score":0.10450000315904617,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.005200000014156103,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7383999824523926},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5863000154495239},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.5465999841690063},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5105000138282776},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.45649999380111694},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4471000134944916},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4424000084400177},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42080000042915344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8011999726295471},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7383999824523926},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5863000154495239},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.5465999841690063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5254999995231628},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5105000138282776},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.45649999380111694},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4471000134944916},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4424000084400177},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.38929998874664307},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.37959998846054077},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36559998989105225},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.296099990606308},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.2946999967098236},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2026.3653122","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653122","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"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3653122","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653122","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W2102605133","https://openalex.org/W2104710929","https://openalex.org/W2504335775","https://openalex.org/W2570343428","https://openalex.org/W2751023760","https://openalex.org/W2802209455","https://openalex.org/W2884561390","https://openalex.org/W2962766617","https://openalex.org/W2963037989","https://openalex.org/W2963351448","https://openalex.org/W2963857746","https://openalex.org/W2964444661","https://openalex.org/W2966401131","https://openalex.org/W2982770724","https://openalex.org/W2989604896","https://openalex.org/W2990763144","https://openalex.org/W3016641475","https://openalex.org/W3018757597","https://openalex.org/W3034971973","https://openalex.org/W3160733999","https://openalex.org/W3179888767","https://openalex.org/W3194790201","https://openalex.org/W4205900964","https://openalex.org/W4229990324","https://openalex.org/W4248936881","https://openalex.org/W4281790833","https://openalex.org/W4382137697","https://openalex.org/W4385760871","https://openalex.org/W4387199878","https://openalex.org/W4394773580","https://openalex.org/W4401056299","https://openalex.org/W6947681574"],"related_works":[],"abstract_inverted_index":{"Unmanned":[0],"aerial":[1],"vehicle":[2],"(UAV)":[3],"target":[4,210],"detection":[5,36,58,202,211,221],"has":[6],"become":[7],"increasingly":[8],"critical":[9],"across":[10,193],"diverse":[11],"applications":[12],"including":[13],"surveillance,":[14],"search":[15],"and":[16,19,31,195],"rescue":[17],"operations,":[18],"autonomous":[20],"navigation.":[21],"While":[22],"the":[23,67,75,88,103,109,120,129,135,145,151,175,182],"YOLO":[24],"series":[25],"models":[26,40],"have":[27],"demonstrated":[28],"exceptional":[29],"efficiency":[30],"real-time":[32],"performance":[33],"in":[34,44,200],"object":[35],"tasks,":[37],"existing":[38],"YOLOv11":[39,78],"still":[41],"exhibit":[42,185],"limitations":[43],"complex":[45,201],"UAV":[46,209,220],"scenarios.":[47,203],"To":[48],"address":[49],"these":[50],"challenges,":[51],"this":[52,125],"paper":[53],"proposes":[54],"YOLOv11-HNU,":[55],"an":[56],"enhanced":[57],"model":[59,123],"incorporating":[60],"two":[61],"key":[62],"innovations.":[63],"First,":[64],"we":[65,86],"integrate":[66],"HFFBlock":[68,110,136,189],"(Hierarchical":[69],"Feature":[70],"Fusion":[71],"Block)":[72],"module":[73,111,137],"into":[74],"neck":[76],"of":[77],"to":[79,96,117,142,155],"enhance":[80],"multi-scale":[81],"feature":[82],"fusion":[83],"capabilities.":[84],"Second,":[85],"implement":[87],"UIOU":[89,146,196],"(Unified":[90],"Intersection":[91],"over":[92,174],"Union)":[93],"loss":[94,147],"function":[95,148],"optimize":[97],"training":[98],"dynamics.":[99],"Experimental":[100],"results":[101],"on":[102],"Roboflow":[104,132],"UAVs":[105],"dataset":[106],"show":[107],"that":[108,181],"alone":[112,149],"improves":[113],"mAP@0.5":[114,139],"from":[115,140],"0.975":[116],"0.978,":[118],"while":[119,144],"complete":[121],"YOLOv11-HNU":[122,159,206],"maintains":[124],"optimal":[126],"performance.":[127],"On":[128],"more":[130],"challenging":[131],"Drone-Kaggle-Data":[133],"dataset,":[134],"increases":[138],"0.944":[141],"0.950,":[143],"achieves":[150,164],"best":[152],"single":[153],"improvement":[154,173,183],"0.957.":[156],"The":[157,204],"final":[158],"model,":[160],"combining":[161],"both":[162],"innovations,":[163],"0.951":[165],"mAP@0.5,":[166],"representing":[167],"a":[168,214],"solid":[169],"0.7":[170],"percentage":[171],"point":[172],"baseline.":[176],"Comprehensive":[177],"ablation":[178],"studies":[179],"reveal":[180],"strategies":[184],"dataset-dependent":[186],"characteristics,":[187],"with":[188],"providing":[190,213],"consistent":[191],"gains":[192],"datasets":[194],"showing":[197],"particular":[198],"effectiveness":[199],"proposed":[205],"effectively":[207],"enhances":[208],"accuracy,":[212],"valuable":[215],"technical":[216],"solution":[217],"for":[218],"real-world":[219],"applications.":[222]},"counts_by_year":[],"updated_date":"2026-01-26T23:06:41.788003","created_date":"2026-01-14T00:00:00"}