{"id":"https://openalex.org/W3095320185","doi":"https://doi.org/10.1109/access.2020.3036075","title":"Multi-Scale Vehicle Detection in High-Resolution Aerial Images With Context Information","display_name":"Multi-Scale Vehicle Detection in High-Resolution Aerial Images With Context Information","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3095320185","doi":"https://doi.org/10.1109/access.2020.3036075","mag":"3095320185"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3036075","doi":"https://doi.org/10.1109/access.2020.3036075","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036075","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09248998.pdf","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,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"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"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09248998.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100779008","display_name":"Xianghui Li","orcid":"https://orcid.org/0000-0001-6266-4783","observed_orcids":["https://orcid.org/0000-0001-6266-4783"]},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianghui Li","raw_affiliation_strings":["Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-6266-4783","affiliations":[{"raw_affiliation_string":"Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010863275","display_name":"Xinde Li","orcid":"https://orcid.org/0000-0002-1529-4537","observed_orcids":["https://orcid.org/0000-0002-1529-4537"]},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinde Li","raw_affiliation_strings":["Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-1529-4537","affiliations":[{"raw_affiliation_string":"Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083939413","display_name":"Hong Pan","orcid":"https://orcid.org/0000-0002-0539-7997","observed_orcids":["https://orcid.org/0000-0002-0539-7997","https://orcid.org/0000-0003-4036-6886"]},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Pan","raw_affiliation_strings":["Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-0539-7997","affiliations":[{"raw_affiliation_string":"Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":{"value":1750,"currency":"USD","value_usd":1750},"apc_paid":{"value":1750,"currency":"USD","value_usd":1750},"fwci":1.3441,"has_fulltext":true,"cited_by_count":31,"citation_normalized_percentile":{"value":0.80170443,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"208643","last_page":"208657"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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":0.9976000189781189,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.0006000000284984708,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.00019999999494757503,"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/vehicle-detection","display_name":"vehicle detection","score":0.9779999852180481},{"id":"https://openalex.org/keywords/aerial-images","display_name":"aerial images","score":0.8889999985694885},{"id":"https://openalex.org/keywords/unmanned-aerial-vehicles","display_name":"unmanned aerial vehicles","score":0.8510000109672546},{"id":"https://openalex.org/keywords/multi-scale-detection","display_name":"multi-scale detection","score":0.8240000009536743},{"id":"https://openalex.org/keywords/high-resolution-imagery","display_name":"high-resolution imagery","score":0.6909999847412109},{"id":"https://openalex.org/keywords/image-cropping","display_name":"image cropping","score":0.7070000171661377},{"id":"https://openalex.org/keywords/contextual-information","display_name":"contextual information","score":0.9380000233650208},{"id":"https://openalex.org/keywords/traffic-monitoring","display_name":"traffic monitoring","score":0.6880000233650208},{"id":"https://openalex.org/keywords/urban-planning","display_name":"urban planning","score":0.7419999837875366}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8078644871711731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7339189648628235},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.7243078947067261},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6152409315109253},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6145749688148499},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6113182902336121},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5815516710281372},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4969060719013214},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.48345550894737244},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46355167031288147},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42823201417922974},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4226454198360443},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3765830397605896},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34798383712768555},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0860576331615448},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.08317488431930542},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3036075","doi":"https://doi.org/10.1109/access.2020.3036075","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036075","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09248998.pdf","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,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"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"},{"id":"pmh:oai:doaj.org/article:68e63faf514b4121b665c59aa6c57a90","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/68e63faf514b4121b665c59aa6c57a90","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 208643-208657 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3036075","doi":"https://doi.org/10.1109/access.2020.3036075","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036075","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09248998.pdf","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,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"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":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G2038491830","display_name":null,"funder_award_id":"62073072","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4103908599","display_name":null,"funder_award_id":"91748106","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7692311763","display_name":"\u878d\u5408\u6d45\u5c42\u6a21\u578b\u548c\u6df1\u5ea6\u7f51\u7edc\u7684\u89c6\u89c9\u7279\u5f81\u5b66\u4e60\u7814\u7a76","funder_award_id":"61671151","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3095320185.pdf","grobid_xml":"https://content.openalex.org/works/W3095320185.grobid-xml"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W61851215","https://openalex.org/W639708223","https://openalex.org/W1483870316","https://openalex.org/W1536680647","https://openalex.org/W1861492603","https://openalex.org/W1910657905","https://openalex.org/W1965877721","https://openalex.org/W2037227137","https://openalex.org/W2043552486","https://openalex.org/W2064022862","https://openalex.org/W2068730032","https://openalex.org/W2072866698","https://openalex.org/W2091224289","https://openalex.org/W2093487233","https://openalex.org/W2102605133","https://openalex.org/W2134650809","https://openalex.org/W2144506857","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2343118941","https://openalex.org/W2407521645","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2582523608","https://openalex.org/W2605995529","https://openalex.org/W2606788270","https://openalex.org/W2736200241","https://openalex.org/W2741763995","https://openalex.org/W2743706233","https://openalex.org/W2788055254","https://openalex.org/W2793872863","https://openalex.org/W2796210376","https://openalex.org/W2796347433","https://openalex.org/W2884275291","https://openalex.org/W2884561390","https://openalex.org/W2894860288","https://openalex.org/W2897981157","https://openalex.org/W2912977378","https://openalex.org/W2915476573","https://openalex.org/W2921849979","https://openalex.org/W2935837427","https://openalex.org/W2944541151","https://openalex.org/W2948656358","https://openalex.org/W2958435308","https://openalex.org/W2962917547","https://openalex.org/W2964241181","https://openalex.org/W2972231924","https://openalex.org/W2982770724","https://openalex.org/W2988452521","https://openalex.org/W2989611864","https://openalex.org/W3003324764","https://openalex.org/W3018757597","https://openalex.org/W3036271496","https://openalex.org/W3106250896","https://openalex.org/W6750227808","https://openalex.org/W6760424586","https://openalex.org/W6777046832"],"related_works":["https://openalex.org/W4404966429","https://openalex.org/W2555441839","https://openalex.org/W2972812228","https://openalex.org/W4399426094","https://openalex.org/W3096450052","https://openalex.org/W4390490232","https://openalex.org/W4390442854","https://openalex.org/W7139989721","https://openalex.org/W3159206453","https://openalex.org/W3198011468"],"abstract_inverted_index":{"Recently,":[0],"unmanned":[1],"aerial":[2,31,85,126],"vehicles":[3,83,93,117,158,181],"(UAV)":[4],"are":[5,204],"widely":[6],"used":[7],"in":[8,30,38,55,61,84,168],"many":[9,45],"fields":[10],"due":[11],"to":[12,76,112,134,175,189,206],"the":[13,21,58,66,70,89,109,114,136,142,147,177,186,208,211],"low":[14],"cost":[15],"and":[16,41,121,150,156,192],"high":[17],"flexibility.":[18],"One":[19],"of":[20,25,69,82,105,116,125,180,210],"most":[22],"popular":[23],"applications":[24],"UAV":[26,71],"is":[27],"vehicle":[28],"detection":[29,90,101],"images":[32],"which":[33,103],"plays":[34],"an":[35,130,198],"important":[36],"role":[37],"traffic":[39],"surveillance":[40],"urban":[42],"planning.":[43],"Although,":[44],"deep":[46],"learning":[47],"based":[48],"detectors":[49,78],"have":[50],"achieved":[51],"state-of-the-art":[52],"(SOTA)":[53],"performance":[54,91],"natural":[56],"images,":[57,127],"significant":[59],"variation":[60],"object":[62],"scales":[63],"caused":[64],"by":[65,214],"altitude":[67],"change":[68],"platform":[72],"brings":[73],"great":[74],"challenges":[75],"these":[77],"for":[79,92],"precise":[80],"localization":[81],"images.":[86],"To":[87],"improve":[88],"with":[94,159,182,216],"different":[95],"scales,":[96],"we":[97,128,145,171,196],"propose":[98,172,197],"a":[99,154,160],"novel":[100],"algorithm":[102,213],"consists":[104],"three":[106],"stages.":[107],"In":[108,141,185],"first":[110],"stage,":[111,144,188],"reduce":[113],"distortion":[115],"during":[118],"image":[119,131,137,149],"resizing":[120],"keep":[122],"more":[123],"information":[124],"utilize":[129],"cropping":[132],"strategy":[133],"divide":[135],"into":[138,153],"two":[139,151],"patches.":[140],"second":[143],"combine":[146],"original":[148],"patches":[152],"batch":[155],"detect":[157],"Convolutional":[161],"Neural":[162],"Network":[163],"(CNN).":[164],"For":[165],"feature":[166],"representation":[167],"our":[169],"detector,":[170],"Scale-specific":[173],"Prediction":[174],"strengthen":[176],"multi-scale":[178],"features":[179],"context":[183],"information.":[184],"final":[187],"fuse":[190],"detections":[191],"suppress":[193],"false":[194],"alarms,":[195],"Outlier-Aware":[199],"Non-Maximum":[200],"Suppression.":[201],"Extensive":[202],"experiments":[203],"conducted":[205],"demonstrate":[207],"superiority":[209],"proposed":[212],"comparison":[215],"other":[217],"SOTA":[218],"solutions.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2020-11-09T00:00:00"}
