{"id":"https://openalex.org/W7224088179","doi":"https://doi.org/10.3390/rs18213705","title":"SA-YOLO: Lightweight Adaptive Small-UAV Detection in Complex Urban Environments","display_name":"SA-YOLO: Lightweight Adaptive Small-UAV Detection in Complex Urban Environments","publication_year":2026,"publication_date":"2026-10-28","ids":{"openalex":"https://openalex.org/W7224088179","doi":"https://doi.org/10.3390/rs18213705"},"language":"en","primary_location":{"id":"doi:10.3390/rs18213705","doi":"https://doi.org/10.3390/rs18213705","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18213705","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/rs18213705","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114860163","display_name":"Xiaotian Zhang","orcid":"https://orcid.org/0000-0003-0574-4095","observed_orcids":["https://orcid.org/0000-0003-0574-4095","https://orcid.org/0009-0002-7031-9546"]},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaotian Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"],"raw_orcid":"https://orcid.org/0009-0002-7031-9546","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125765897","display_name":"Longmiao Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Longmiao Chen","raw_affiliation_strings":["School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160046397","display_name":"Chao Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Wang","raw_affiliation_strings":["School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127979038","display_name":"Hongbin Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongbin Chen","raw_affiliation_strings":["School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5159988241","display_name":"Jiaqi Hou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Hou","raw_affiliation_strings":["School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5125765897"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":{"value":2700,"currency":"CHF","value_usd":3258},"apc_paid":{"value":2700,"currency":"CHF","value_usd":3258},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.7713967,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"21","first_page":"3705","last_page":"3705"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9990000128746033,"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":0.9990000128746033,"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":0.0003000000142492354,"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":9.999999747378752e-05,"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/anti-uav","display_name":"anti-UAV","score":0.6650000214576721},{"id":"https://openalex.org/keywords/lightweight-object-detection","display_name":"lightweight object detection","score":0.7450000047683716},{"id":"https://openalex.org/keywords/yolo","display_name":"YOLO","score":0.8119999766349792},{"id":"https://openalex.org/keywords/dynamic-upsampling","display_name":"dynamic upsampling","score":0.7770000100135803},{"id":"https://openalex.org/keywords/wasserstein-distance-loss","display_name":"Wasserstein distance loss","score":0.8949999809265137},{"id":"https://openalex.org/keywords/bounding-box-regression","display_name":"bounding box regression","score":0.8410000205039978},{"id":"https://openalex.org/keywords/real-time-detection","display_name":"real-time detection","score":0.6570000052452087},{"id":"https://openalex.org/keywords/small-object-detection","display_name":"small object detection","score":0.4740000069141388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7573999762535095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6394000053405762},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.5938000082969666},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.583899974822998},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5264999866485596},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5138000249862671},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4893999993801117},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45989999175071716},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.45019999146461487},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41429999470710754},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3806000053882599},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.3538999855518341},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.35350000858306885},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.33899998664855957},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33889999985694885},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.32589998841285706},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3239000141620636},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.3109999895095825},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.2685999870300293},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.25609999895095825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/rs18213705","doi":"https://doi.org/10.3390/rs18213705","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18213705","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/rs18213705","doi":"https://doi.org/10.3390/rs18213705","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18213705","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6798999905586243}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2193145675","https://openalex.org/W2752782242","https://openalex.org/W2884585870","https://openalex.org/W2950628590","https://openalex.org/W2962858109","https://openalex.org/W2987322772","https://openalex.org/W2997747012","https://openalex.org/W3034421924","https://openalex.org/W3034552520","https://openalex.org/W3035414587","https://openalex.org/W3036046236","https://openalex.org/W3177052299","https://openalex.org/W3194790201","https://openalex.org/W4213147678","https://openalex.org/W4281487654","https://openalex.org/W4372347372","https://openalex.org/W4386303392","https://openalex.org/W4390873058","https://openalex.org/W4392950102","https://openalex.org/W4399297196","https://openalex.org/W4402402063","https://openalex.org/W4402754006","https://openalex.org/W4403770406","https://openalex.org/W4407640624","https://openalex.org/W4408360617","https://openalex.org/W4409303595","https://openalex.org/W4411225352","https://openalex.org/W4412981088","https://openalex.org/W4415795831","https://openalex.org/W4416922411","https://openalex.org/W7127368577","https://openalex.org/W7134169674","https://openalex.org/W7136082557","https://openalex.org/W7140178087","https://openalex.org/W7155209800","https://openalex.org/W7160165532","https://openalex.org/W7167475464"],"related_works":["https://openalex.org/W7201880543","https://openalex.org/W7164811332","https://openalex.org/W7214706308","https://openalex.org/W7203628791","https://openalex.org/W4415283323","https://openalex.org/W7201831194","https://openalex.org/W7117421059","https://openalex.org/W7207515417","https://openalex.org/W7208792491","https://openalex.org/W7141280290"],"abstract_inverted_index":{"Visual":[0],"detection":[1,63],"of":[2,12,106,141],"unmanned":[3],"aerial":[4],"vehicles":[5],"(UAVs)":[6],"is":[7,164,174],"an":[8],"essential":[9],"perception":[10],"component":[11],"urban":[13,22],"low-altitude":[14],"security":[15],"systems.":[16],"However,":[17],"UAV":[18],"targets":[19],"in":[20,190],"complex":[21],"scenes":[23],"appear":[24],"small":[25,127],"and":[26,38,41,48,132,143],"exhibit":[27],"weak":[28],"visual":[29],"features.":[30],"Existing":[31],"convolutional":[32],"structures":[33],"inadequately":[34],"extract":[35],"their":[36],"contours":[37],"fine-grained":[39],"details,":[40],"background":[42],"clutter":[43],"such":[44],"as":[45],"building":[46],"textures":[47],"trees":[49],"attenuates":[50],"target":[51,76],"feature":[52],"responses.":[53],"To":[54],"address":[55],"these":[56],"problems,":[57],"this":[58],"paper":[59],"proposes":[60],"a":[61,96,191,196,201],"lightweight":[62],"model,":[64,194],"SA-YOLO":[65,137,186],"(Small-target":[66],"Adaptive":[67],"YOLO).":[68],"A":[69,113],"bilateral":[70],"detail":[71],"refinement":[72],"convolution":[73],"(BDRConv)":[74],"strengthens":[75],"details":[77],"while":[78],"preserving":[79],"primary":[80],"features":[81,108],"through":[82,109],"dual-branch":[83],"collaboration.":[84],"An":[85],"adaptive":[86],"SimAM":[87],"(ASimAM)":[88],"attention":[89,92],"mechanism":[90],"modulates":[91],"response":[93],"strength":[94],"via":[95],"learnable":[97],"scaling":[98],"factor.":[99],"DySample":[100],"dynamic":[101],"upsampling":[102],"achieves":[103,138],"sub-pixel-level":[104],"reconstruction":[105],"cross-scale":[107],"content-adaptive":[110],"sampling":[111],"offsets.":[112],"weighted":[114],"joint":[115],"loss":[116],"based":[117],"on":[118,167,170],"the":[119,130,133,158,162,172,183],"normalized":[120],"Wasserstein":[121],"distance":[122],"improves":[123],"bounding-box":[124],"regression":[125],"for":[126],"targets.":[128],"On":[129],"DUT-Anti-UAV":[131],"self-constructed":[134],"C-UAV":[135,171],"datasets,":[136],"mAP50-95":[139,159],"values":[140],"52.1%":[142],"43.2%,":[144],"respectively,":[145],"with":[146,182],"only":[147],"2.41":[148],"M":[149],"parameters":[150],"at":[151,200],"171":[152],"FPS.":[153],"Across":[154],"five":[155],"training":[156],"seeds,":[157],"improvement":[160],"over":[161],"baseline":[163],"statistically":[165,179],"significant":[166],"DUT-Anti-UAV,":[168],"whereas":[169],"gain":[173],"directionally":[175],"consistent":[176],"but":[177],"not":[178],"significant.":[180],"Compared":[181],"accuracy-leading":[184],"detectors,":[185],"delivers":[187],"comparable":[188],"accuracy":[189],"more":[192],"compact":[193],"achieving":[195],"favorable":[197],"accuracy\u2013model-size":[198],"tradeoff":[199],"real-time":[202],"inference":[203],"speed.":[204]},"counts_by_year":[],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2026-10-29T00:00:00"}
