{"id":"https://openalex.org/W7117131298","doi":"https://doi.org/10.1145/3773276.3774297","title":"Dual-Modality UAV Detection and Classification under Low-Visibility: A Synth-Real RGB\u2013IR Dataset and Benchmark for Aerial Surveillance","display_name":"Dual-Modality UAV Detection and Classification under Low-Visibility: A Synth-Real RGB\u2013IR Dataset and Benchmark for Aerial Surveillance","publication_year":2025,"publication_date":"2025-12-01","ids":{"openalex":"https://openalex.org/W7117131298","doi":"https://doi.org/10.1145/3773276.3774297"},"language":null,"primary_location":{"id":"doi:10.1145/3773276.3774297","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773276.3774297","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3773276.3774297?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the IEEE/ACM 12th International Conference on Big Data Computing, Applications and Technologies","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3773276.3774297?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121203089","display_name":"Hatoun Alshoail","orcid":null},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Hatoun Alshoail","raw_affiliation_strings":["Department of Computer Sciences;College of Computer and Information Sciences;Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0009-0002-5772-7211","affiliations":[{"raw_affiliation_string":"Department of Computer Sciences;College of Computer and Information Sciences;Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121178856","display_name":"Sarah Alruwais","orcid":null},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Sarah Alruwais","raw_affiliation_strings":["Department of Computer Sciences;College of Computer and Information Sciences;Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0009-0006-6172-8910","affiliations":[{"raw_affiliation_string":"Department of Computer Sciences;College of Computer and Information Sciences;Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121239741","display_name":"Juri Alqorashi","orcid":null},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Juri Alqorashi","raw_affiliation_strings":["Department of Computer Sciences;College of Computer and Information Sciences;Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0009-0001-5291-2154","affiliations":[{"raw_affiliation_string":"Department of Computer Sciences;College of Computer and Information Sciences;Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059877458","display_name":"Najah Alsubaie","orcid":"https://orcid.org/0000-0002-6381-9019"},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Najah Alsubaie","raw_affiliation_strings":["College of Computer and Information Sciences Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-6381-9019","affiliations":[{"raw_affiliation_string":"College of Computer and Information Sciences Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5121203089"],"corresponding_institution_ids":["https://openalex.org/I106778892"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.70962042,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.8108000159263611,"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"}},"topics":[{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.8108000159263611,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.08250000327825546,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.01549999974668026,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/benchmarking","display_name":"Benchmarking","score":0.6790000200271606},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5658000111579895},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5594000220298767},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5029000043869019},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.48820000886917114},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.41819998621940613},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.40880000591278076},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4025999903678894},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3959999978542328}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7057999968528748},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6790000200271606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6180999875068665},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5658000111579895},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5594000220298767},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5029000043869019},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.48820000886917114},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41819998621940613},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.40880000591278076},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4025999903678894},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.39250001311302185},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37209999561309814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34360000491142273},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C34872919","wikidata":"https://www.wikidata.org/wiki/Q7092302","display_name":"One-class classification","level":3,"score":0.3296000063419342},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3264000117778778},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.3253999948501587},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.30480000376701355},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C2780836893","wikidata":"https://www.wikidata.org/wiki/Q19922674","display_name":"Fire detection","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C112789634","wikidata":"https://www.wikidata.org/wiki/Q18207010","display_name":"False positives and false negatives","level":3,"score":0.2800999879837036},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3773276.3774297","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773276.3774297","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3773276.3774297?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the IEEE/ACM 12th International Conference on Big Data Computing, Applications and Technologies","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3773276.3774297","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773276.3774297","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3773276.3774297?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the IEEE/ACM 12th International Conference on Big Data Computing, Applications and Technologies","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W7117131298.pdf"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1910108985","https://openalex.org/W2194775991","https://openalex.org/W2803009534","https://openalex.org/W2889985731","https://openalex.org/W2963201472","https://openalex.org/W2968819645","https://openalex.org/W2975208387","https://openalex.org/W3207919963","https://openalex.org/W3214549945","https://openalex.org/W4281487654","https://openalex.org/W4307411363","https://openalex.org/W4317888526","https://openalex.org/W4319796192","https://openalex.org/W4323666945","https://openalex.org/W4383109290","https://openalex.org/W4386303392","https://openalex.org/W4387490528","https://openalex.org/W4390231943","https://openalex.org/W4392188507","https://openalex.org/W4400876760","https://openalex.org/W4402320264","https://openalex.org/W4403738039"],"related_works":[],"abstract_inverted_index":{"This":[0],"work":[1,31],"presents":[2],"a":[3,37,62,87],"dual-modality":[4],"unmanned":[5],"aerial":[6,18],"vehicle":[7],"(UAV)":[8],"detection":[9,91,165],"and":[10,22,45,53,77,92,114,124,135,160],"classification":[11,93,132],"approach":[12,129],"designed":[13],"to":[14,80,139],"address":[15],"challenges":[16],"in":[17],"surveillance":[19],"under":[20],"low-visibility":[21],"cluttered":[23],"environmental":[24],"conditions.":[25],"The":[26,57,127],"core":[27],"contributions":[28],"of":[29,90,122,146],"this":[30,96],"are":[32],"twofold.":[33],"First,":[34],"we":[35,85],"introduce":[36],"novel,":[38],"high-quality":[39],"multimodal":[40],"dataset":[41,58],"comprising":[42],"both":[43],"real-world":[44],"synthetically":[46],"generated":[47],"UAV":[48,137],"imagery":[49],"across":[50],"red-green-blue":[51],"(RGB)":[52,159],"infrared":[54],"(IR)":[55],"channels.":[56],"was":[59],"curated":[60],"through":[61],"rigorous":[63],"pipeline":[64],"that":[65],"includes":[66],"multi-source":[67],"video":[68],"collection,":[69],"frame":[70],"extraction,":[71],"noise":[72],"reduction,":[73],"simulation-based":[74],"class":[75],"balancing,":[76],"scene-aware":[78],"clustering":[79],"prevent":[81],"data":[82],"leakage.":[83],"Second,":[84],"present":[86],"comprehensive":[88],"benchmarking":[89],"models":[94,99],"using":[95,102],"dataset.":[97],"Detection":[98],"were":[100],"fine-tuned":[101],"You":[103],"Only":[104],"Look":[105],"Once":[106],"Version":[107],"11":[108],"Nano":[109],"(YOLOv11n),":[110],"one":[111],"for":[112,116],"RGB":[113],"another":[115],"IR,":[117],"achieving":[118],"[email":[119],"protected]":[120],"scores":[121],"93.5%":[123],"98.2%,":[125],"respectively.":[126],"proposed":[128],"also":[130],"performs":[131],"into":[133],"fixed-wing":[134],"rotary-wing":[136],"types":[138],"support":[140],"more":[141],"informed":[142],"threat":[143],"evaluation.":[144],"Integration":[145],"the":[147],"Slicing":[148],"Aided":[149],"Hyper":[150],"Inference":[151],"(SAHI)":[152],"framework":[153],"increased":[154],"true":[155],"positives":[156],"by":[157],"24.7%":[158],"2.4%":[161],"(IR),":[162],"significantly":[163],"enhancing":[164],"performance.":[166]},"counts_by_year":[],"updated_date":"2026-03-11T06:11:40.159057","created_date":"2025-12-24T00:00:00"}