{"id":"https://openalex.org/W4389104823","doi":"https://doi.org/10.1109/jstars.2023.3335283","title":"Faster Transformer-DS: Multiscale Vehicle Detection of Remote-Sensing Images Based on Transformer and Distance-Scale Loss","display_name":"Faster Transformer-DS: Multiscale Vehicle Detection of Remote-Sensing Images Based on Transformer and Distance-Scale Loss","publication_year":2023,"publication_date":"2023-11-28","ids":{"openalex":"https://openalex.org/W4389104823","doi":"https://doi.org/10.1109/jstars.2023.3335283"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2023.3335283","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2023.3335283","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/10329917.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/10329917.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102717059","display_name":"Jiahuan Zhang","orcid":"https://orcid.org/0009-0007-4598-9018"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiahuan Zhang","raw_affiliation_strings":["School of Geodesy and Geomatics, Wuhan University, Wuhan, China","School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102927497","display_name":"H. B. Liu","orcid":"https://orcid.org/0009-0001-5307-2660"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengzhen Liu","raw_affiliation_strings":["School of Geodesy and Geomatics, Wuhan University, Wuhan, China","School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100388370","display_name":"Yi Zhang","orcid":"https://orcid.org/0009-0008-4946-7820"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhang","raw_affiliation_strings":["School of Geodesy and Geomatics, Wuhan University, Wuhan, China","School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100743029","display_name":"Menghan Li","orcid":"https://orcid.org/0009-0001-2192-0768"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Menghan Li","raw_affiliation_strings":["School of Geodesy and Geomatics, Wuhan University, Wuhan, China","School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027395360","display_name":"Zongqian Zhan","orcid":"https://orcid.org/0009-0000-9305-3141"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongqian Zhan","raw_affiliation_strings":["School of Geodesy and Geomatics, Wuhan University, Wuhan, China","School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102717059"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":0.8609,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.76195273,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"17","issue":null,"first_page":"1961","last_page":"1975"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.996999979019165,"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":0.9912999868392944,"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/minimum-bounding-box","display_name":"Minimum bounding box","score":0.8236570358276367},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.705297589302063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6671671271324158},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6306322813034058},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5852375030517578},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5483834743499756},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5169281363487244},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5111590027809143},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5075467824935913},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5044301748275757},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.48348456621170044},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19249475002288818},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09594595432281494},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.08926334977149963}],"concepts":[{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.8236570358276367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.705297589302063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6671671271324158},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6306322813034058},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5852375030517578},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5483834743499756},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5169281363487244},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5111590027809143},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5075467824935913},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5044301748275757},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.48348456621170044},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19249475002288818},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09594595432281494},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.08926334977149963},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2023.3335283","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2023.3335283","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/10329917.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1be16103873f48188c46e35d0b30f0f2","is_oa":true,"landing_page_url":"https://doaj.org/article/1be16103873f48188c46e35d0b30f0f2","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 1961-1975 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2023.3335283","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2023.3335283","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/10329917.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4151751101","display_name":null,"funder_award_id":"61871295","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389104823.pdf","grobid_xml":"https://content.openalex.org/works/W4389104823.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W2036329542","https://openalex.org/W2478285118","https://openalex.org/W2504335775","https://openalex.org/W2565639579","https://openalex.org/W2586661295","https://openalex.org/W2956902387","https://openalex.org/W2962721361","https://openalex.org/W2962749812","https://openalex.org/W2962766617","https://openalex.org/W2962834855","https://openalex.org/W2963299996","https://openalex.org/W2963786238","https://openalex.org/W2964241181","https://openalex.org/W2997747012","https://openalex.org/W3012303644","https://openalex.org/W3081327309","https://openalex.org/W3107867277","https://openalex.org/W3122173535","https://openalex.org/W3122799380","https://openalex.org/W3134487554","https://openalex.org/W3138516171","https://openalex.org/W3157042932","https://openalex.org/W3171398643","https://openalex.org/W3175515048","https://openalex.org/W3208154594","https://openalex.org/W4249736682","https://openalex.org/W4288325606","https://openalex.org/W4293584584","https://openalex.org/W6733240366","https://openalex.org/W6750227808","https://openalex.org/W6764322716","https://openalex.org/W6766183005","https://openalex.org/W6802878479"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W4287027631","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"Vehicle":[0],"Detection":[1],"(VD)":[2],"on":[3,220],"Remote-Sensing":[4],"(RS)":[5],"images":[6,222],"has":[7],"gained":[8],"impressive":[9],"achievements":[10],"these":[11],"years,":[12],"mainly":[13],"thanks":[14],"to":[15,123,134,157,180,205,253],"the":[16,124,137,158,162,167,176,181,186,190,196,209,214,224],"development":[17],"of":[18,93,139,161,166,198,216,228],"popular":[19],"learning-based":[20],"object":[21,114],"detection":[22,36,79,219,238,256],"architectures":[23],"(e.g.,":[24],"Faster":[25],"R-CNN,":[26],"YOLO":[27],"series,":[28],"etc.).":[29],"However,":[30],"for":[31,58,112],"RS":[32,221],"images,":[33],"muti-scale":[34],"vehicle":[35,218],"with":[37,54,171],"tiny":[38,46],"size":[39],"still":[40],"remains":[41],"challenging.":[42],"Particularly,":[43],"vehicles":[44],"as":[45,108],"objects":[47],"typically":[48],"contain":[49],"only":[50],"a":[51,77,97,145],"few":[52],"pixels":[53],"very":[55],"rare":[56],"information":[57],"model":[59,80,249],"training":[60],"and":[61,69,89,116,127,164,189,223,236,246],"validation,":[62],"which":[63,84,229],"can":[64,101,212],"result":[65],"in":[66,83],"inaccurate":[67],"localization":[68,138],"intricate":[70],"classification.":[71],"In":[72,121],"this":[73],"paper,":[74],"we":[75,143],"present":[76],"new":[78],"called":[81],"Faster-Transformer-DS,":[82],"two":[85],"improvements":[86],"are":[87,203,230,244],"proposed":[88,144,210],"discussed:":[90],"(1)":[91],"instead":[92],"CNN":[94],"based":[95],"ResNet50,":[96],"Transformer-based":[98],"backbone\u2014PVTv2-b0":[99],"that":[100,207],"extract":[102],"global":[103],"context":[104],"information,":[105],"is":[106,154,250],"investigated":[107],"feature":[109],"extraction":[110],"backbone":[111],"both":[113,208],"classification":[115],"bounding":[117,141,168,187],"box":[118,169,188],"regression.":[119],"(2)":[120],"contrast":[122],"conventional":[125],"paradigm-based":[126],"IoU":[128],"(Intersection":[129],"over":[130],"Union)-based":[131],"loss":[132,148,153,178],"functions,":[133],"further":[135],"fine-tune":[136],"predicted":[140],"box,":[142],"novel":[146],"distance-scale":[147],"(DS":[149],"Loss)":[150],"function\u2014the":[151],"distance":[152],"directly":[155],"related":[156],"absolute":[159],"value":[160],"length":[163],"width":[165],"together":[170],"its":[172],"center":[173],"position,":[174],"while":[175],"scale":[177],"refers":[179],"geometric":[182],"shape":[183],"ratio":[184],"between":[185],"ground":[191],"truth":[192],"box.":[193],"To":[194],"demonstrate":[195],"efficacy":[197],"our":[199,248],"model,":[200],"comprehensive":[201],"experiments":[202],"conducted":[204],"show":[206],"methods":[211,243],"boost":[213],"performance":[215],"multi-scale":[217],"best":[225],"result,":[226],"all":[227],"confirmed":[231],"by":[232],"experimental":[233],"data":[234],"indicators":[235],"visual":[237],"results.":[239],"Additionally,":[240],"several":[241],"state-of-the-art":[242],"compared":[245],"consequently,":[247],"notably":[251],"superior":[252],"many":[254],"common":[255],"models.":[257]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}