{"id":"https://openalex.org/W7123343258","doi":"https://doi.org/10.1109/dsa66321.2025.00039","title":"Semantic-Enhanced Image Object Detection in Unmanned Aerial Vehicle Imagery","display_name":"Semantic-Enhanced Image Object Detection in Unmanned Aerial Vehicle Imagery","publication_year":2025,"publication_date":"2025-11-24","ids":{"openalex":"https://openalex.org/W7123343258","doi":"https://doi.org/10.1109/dsa66321.2025.00039"},"language":null,"primary_location":{"id":"doi:10.1109/dsa66321.2025.00039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsa66321.2025.00039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 12th International Conference on Dependable Systems and Their Applications (DSA)","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/A5122865205","display_name":"Li Mai","orcid":null},"institutions":[{"id":"https://openalex.org/I118987531","display_name":"Anhui Jianzhu University","ror":"https://ror.org/0108wjw08","country_code":"CN","type":"education","lineage":["https://openalex.org/I118987531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Mai","raw_affiliation_strings":["Anhui Mingsheng Hengzhuo Technology Co., Ltd.,Power Grid Digitalization Division,Hefei,Anhui,China"],"affiliations":[{"raw_affiliation_string":"Anhui Mingsheng Hengzhuo Technology Co., Ltd.,Power Grid Digitalization Division,Hefei,Anhui,China","institution_ids":["https://openalex.org/I118987531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122862929","display_name":"Chen Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I118987531","display_name":"Anhui Jianzhu University","ror":"https://ror.org/0108wjw08","country_code":"CN","type":"education","lineage":["https://openalex.org/I118987531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Dai","raw_affiliation_strings":["Anhui Mingsheng Hengzhuo Technology Co., Ltd.,System Integration Division,Hefei,Anhui,China"],"affiliations":[{"raw_affiliation_string":"Anhui Mingsheng Hengzhuo Technology Co., Ltd.,System Integration Division,Hefei,Anhui,China","institution_ids":["https://openalex.org/I118987531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122864621","display_name":"Rui Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I118987531","display_name":"Anhui Jianzhu University","ror":"https://ror.org/0108wjw08","country_code":"CN","type":"education","lineage":["https://openalex.org/I118987531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Dai","raw_affiliation_strings":["Anhui Mingsheng Hengzhuo Technology Co., Ltd.,System Integration Division,Hefei,Anhui,China"],"affiliations":[{"raw_affiliation_string":"Anhui Mingsheng Hengzhuo Technology Co., Ltd.,System Integration Division,Hefei,Anhui,China","institution_ids":["https://openalex.org/I118987531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122864372","display_name":"Heyi Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I118987531","display_name":"Anhui Jianzhu University","ror":"https://ror.org/0108wjw08","country_code":"CN","type":"education","lineage":["https://openalex.org/I118987531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heyi Liu","raw_affiliation_strings":["Anhui Mingsheng Hengzhuo Technology Co., Ltd.,System Integration Division,Hefei,Anhui,China"],"affiliations":[{"raw_affiliation_string":"Anhui Mingsheng Hengzhuo Technology Co., Ltd.,System Integration Division,Hefei,Anhui,China","institution_ids":["https://openalex.org/I118987531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074918928","display_name":"Y Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I118987531","display_name":"Anhui Jianzhu University","ror":"https://ror.org/0108wjw08","country_code":"CN","type":"education","lineage":["https://openalex.org/I118987531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yeming Ding","raw_affiliation_strings":["Anhui Mingsheng Hengzhuo Technology Co., Ltd.,System Integration Division,Hefei,Anhui,China"],"affiliations":[{"raw_affiliation_string":"Anhui Mingsheng Hengzhuo Technology Co., Ltd.,System Integration Division,Hefei,Anhui,China","institution_ids":["https://openalex.org/I118987531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5122865205"],"corresponding_institution_ids":["https://openalex.org/I118987531"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.6971928,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"269","last_page":"275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7573999762535095,"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":0.7573999762535095,"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":0.051899999380111694,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.02630000002682209,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7214999794960022},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6463000178337097},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6218000054359436},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.4404999911785126},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.36959999799728394},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.35589998960494995},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.34869998693466187},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.33399999141693115},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3240000009536743}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7728000283241272},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7526999711990356},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7214999794960022},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6463000178337097},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6218000054359436},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6154999732971191},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.4404999911785126},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.34869998693466187},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3240000009536743},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.32019999623298645},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3183000087738037},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.3158999979496002},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2754000127315521},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.25200000405311584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsa66321.2025.00039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsa66321.2025.00039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 12th International Conference on Dependable Systems and Their Applications (DSA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6843574643135071,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Unmanned":[0],"Aerial":[1],"Vehicles":[2],"(UAVs)":[3],"have":[4],"emerged":[5],"as":[6,68],"powerful":[7],"and":[8,22,26,47,78,92,101,151,186,207,228,242],"flexible":[9],"platforms":[10],"for":[11,126],"a":[12,60,111,121,141,190],"wide":[13],"range":[14],"of":[15,32,45,50,95],"intelligent":[16],"vision":[17],"applications,":[18],"including":[19,226],"surveillance,":[20],"search":[21],"rescue,":[23],"environmental":[24],"monitoring,":[25],"traffic":[27],"analysis.":[28],"At":[29],"the":[30,42,90,132,147,163,173,177,198],"core":[31],"these":[33,106],"applications":[34],"lies":[35],"Visual":[36],"Object":[37],"Detection":[38,122],"(VOD),":[39],"which":[40],"provides":[41],"fundamental":[43],"capability":[44],"identifying":[46],"localizing":[48],"objects":[49,241],"interest":[51],"from":[52,162],"aerial":[53,84,157],"imagery.":[54,128],"However,":[55],"UAV-based":[56],"visual":[57,148],"detection":[58,113,234],"remains":[59],"highly":[61],"challenging":[62,156],"problem":[63],"due":[64],"to":[65,145,179,200,204],"factors":[66],"such":[67],"drastic":[69],"object":[70,182,208],"scale":[71],"variation,":[72],"frequent":[73],"occlusions,":[74],"complex":[75],"background":[76],"clutter,":[77],"motion-induced":[79],"distortions":[80],"caused":[81],"by":[82],"dynamic":[83],"viewpoints.":[85],"These":[86],"challenges":[87],"significantly":[88],"degrade":[89],"robustness":[91],"generalization":[93],"ability":[94],"existing":[96],"detectors,":[97],"particularly":[98,236],"in":[99,189,237],"small-object":[100],"high-altitude":[102],"scenes.":[103],"To":[104],"overcome":[105],"limitations,":[107],"this":[108],"paper":[109],"introduces":[110],"semantic-enhanced":[112],"framework":[114],"that":[115],"integrates":[116],"text-guided":[117],"semantic":[118,160],"priors":[119],"into":[120],"Transformer":[123],"(DETR)-based":[124],"architecture":[125],"UAV":[127,224],"Leveraging":[129],"multimodal":[130,195],"learning,":[131],"proposed":[133,216],"method":[134,217],"incorporates":[135],"high-level":[136],"textual":[137],"descriptions":[138],"extracted":[139],"via":[140],"pretrained":[142],"vision-language":[143],"model":[144,199],"enrich":[146],"feature":[149],"representation":[150],"enhance":[152],"discriminative":[153],"capacity":[154],"under":[155],"conditions.":[158],"Specifically,":[159],"embeddings":[161],"text":[164],"modality":[165],"are":[166],"fused":[167],"with":[168],"multiscale":[169],"image":[170],"features":[171],"within":[172],"transformer":[174],"encoder,":[175],"enabling":[176],"detector":[178],"reason":[180],"about":[181],"semantics,":[183],"contextual":[184],"relationships,":[185],"category":[187],"dependencies":[188],"unified":[191],"end-toend":[192],"manner.":[193],"This":[194],"enhancement":[196],"enables":[197],"adapt":[201],"more":[202],"effectively":[203],"varying":[205],"scenes":[206],"scales":[209],"without":[210],"requiring":[211],"extensive":[212],"manual":[213],"tuning.":[214],"The":[215],"is":[218],"extensively":[219],"validated":[220],"on":[221],"multiple":[222],"benchmark":[223],"datasets,":[225],"VisDrone-2019":[227],"UAVVaste,":[229],"where":[230],"it":[231],"demonstrates":[232],"superior":[233],"performance,":[235],"scenarios":[238],"involving":[239],"small":[240],"dense":[243],"occlusions.":[244]},"counts_by_year":[],"updated_date":"2026-02-23T20:09:44.859080","created_date":"2026-01-14T00:00:00"}
