{"id":"https://openalex.org/W7125939784","doi":"https://doi.org/10.1109/smc58881.2025.11343074","title":"SIEP-YOLO: Small Target Cluster Detection in Aerial Images","display_name":"SIEP-YOLO: Small Target Cluster Detection in Aerial Images","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125939784","doi":"https://doi.org/10.1109/smc58881.2025.11343074"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11343074","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-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":"https://openalex.org/A5123745464","display_name":"Peiyao Liu","orcid":null},"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":"Peiyao Liu","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Automation,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Automation,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124129260","display_name":"Jun Wang","orcid":null},"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":"Jun Wang","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Automation,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Automation,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082398400","display_name":"Jinpeng Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092002","display_name":"Runze (China)","ror":"https://ror.org/00fgwkr80","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210092002"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinpeng Hu","raw_affiliation_strings":["Chongqing Jianshe Industry,Chongqing,China"],"affiliations":[{"raw_affiliation_string":"Chongqing Jianshe Industry,Chongqing,China","institution_ids":["https://openalex.org/I4210092002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124124936","display_name":"Huanyu Yang","orcid":null},"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":"Huanyu Yang","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Automation,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Automation,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124142510","display_name":"Peng Zhu","orcid":null},"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":"Peng Zhu","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Economics and Management,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Economics and Management,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054582718","display_name":"Yuming Bo","orcid":null},"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":"Yuming Bo","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Automation,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Automation,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5123745464"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.7161631,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7750","last_page":"7755"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.597599983215332,"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":0.597599983215332,"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":0.12099999934434891,"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/T11133","display_name":"UAV Applications and Optimization","score":0.03889999911189079,"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":0.7883999943733215},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5942999720573425},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5697000026702881},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5544999837875366},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5435000061988831},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5268999934196472},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.5245000123977661},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.4381999969482422}],"concepts":[{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7883999943733215},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.738099992275238},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5942999720573425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5903000235557556},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5697000026702881},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5544999837875366},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5435000061988831},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5268999934196472},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.5245000123977661},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44690001010894775},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.4381999969482422},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3874000012874603},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.3562000095844269},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.3490999937057495},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27950000762939453},{"id":"https://openalex.org/C3019973339","wikidata":"https://www.wikidata.org/wiki/Q899523","display_name":"Object based","level":3,"score":0.27950000762939453},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C182521987","wikidata":"https://www.wikidata.org/wiki/Q2493877","display_name":"Viola\u2013Jones object detection framework","level":5,"score":0.26669999957084656},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.260699987411499},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11343074","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2899607431","https://openalex.org/W2962766044","https://openalex.org/W2964444661","https://openalex.org/W2969875432","https://openalex.org/W2993756598","https://openalex.org/W2996735448","https://openalex.org/W2997408160","https://openalex.org/W3034268345","https://openalex.org/W3034971973","https://openalex.org/W3036543015","https://openalex.org/W3046838151","https://openalex.org/W3094897602","https://openalex.org/W3175630421","https://openalex.org/W4312823573","https://openalex.org/W4402716243","https://openalex.org/W4410296777"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"detection":[1,29,88,97],"of":[2],"small":[3,34,86,143],"object":[4,28,87,144],"clusters":[5],"in":[6,125,153],"modern":[7],"security":[8],"surveillance":[9,152],"systems":[10],"is":[11],"critical":[12],"for":[13,142],"threat":[14],"prevention":[15],"and":[16,22,47,56,83,96,109,123,127,150],"response,":[17],"directly":[18],"impacting":[19],"monitoring":[20],"efficiency":[21],"risk":[23],"management":[24],"efficacy.":[25],"However,":[26],"prevailing":[27],"algorithms":[30],"struggle":[31],"with":[32],"high-density":[33],"target":[35],"scenarios,":[36],"suffering":[37],"from":[38],"slow":[39],"inference":[40],"speeds,":[41],"insufficient":[42],"precision,":[43],"frequent":[44],"false":[45],"positives,":[46],"high":[48,107],"miss":[49],"rates.":[50],"These":[51],"limitations":[52],"undermine":[53],"real-time":[54],"reliability":[55],"responsiveness":[57],"to":[58],"emergencies.":[59],"To":[60],"address":[61],"these":[62],"challenges,":[63],"we":[64],"propose":[65],"SIEP-YOLO,":[66],"an":[67],"enhanced":[68],"YOLOv11-based":[69],"model":[70,135],"integrating":[71],"three":[72],"novel":[73],"components:":[74],"the":[75,118],"SDI-iAFF":[76],"feature":[77],"fusion":[78],"module,":[79,82],"EUCB":[80],"upsampling":[81],"a":[84,104,139],"specialized":[85],"layer":[89],"P2.":[90],"This":[91],"architecture":[92],"boosts":[93],"representational":[94],"capacity":[95],"performance":[98],"while":[99],"simplifying":[100],"computational":[101],"complexity,":[102],"achieving":[103],"balance":[105],"between":[106],"accuracy":[108],"lightweight":[110],"design.":[111],"Experimental":[112],"results":[113],"demonstrate":[114],"that":[115],"SIEP-YOLO":[116],"outperforms":[117],"original":[119],"YOLOv11":[120],"by":[121],"3.2%":[122],"2.0%":[124],"mAP@0.5":[126],"mAP@(0.5:0.95),":[128],"respectively,":[129],"on":[130],"benchmark":[131],"datasets.":[132],"The":[133],"proposed":[134],"thus":[136],"emerges":[137],"as":[138],"superior":[140],"solution":[141],"cluster":[145],"detection,":[146],"enabling":[147],"more":[148],"efficient":[149],"reliable":[151],"complex":[154],"environments.":[155]},"counts_by_year":[],"updated_date":"2026-01-29T23:17:01.242718","created_date":"2026-01-29T00:00:00"}