{"id":"https://openalex.org/W7150743919","doi":"https://doi.org/10.1016/j.engappai.2026.114626","title":"Improved noising training detection Transformer based drone image detector","display_name":"Improved noising training detection Transformer based drone image detector","publication_year":2026,"publication_date":"2026-04-06","ids":{"openalex":"https://openalex.org/W7150743919","doi":"https://doi.org/10.1016/j.engappai.2026.114626"},"language":"en","primary_location":{"id":"doi:10.1016/j.engappai.2026.114626","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114626","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.engappai.2026.114626","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133023872","display_name":"Lu Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu Ding","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-6316-8527","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104148848","display_name":"Jinghua Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinghua Deng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005666731","display_name":"Xun Huang","orcid":"https://orcid.org/0000-0001-7415-3307"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xun Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133048055","display_name":"Yong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yong Wang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-2266-214X","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5133048055"],"corresponding_institution_ids":[],"apc_list":{"value":3170,"currency":"USD","value_usd":3170},"apc_paid":{"value":3170,"currency":"USD","value_usd":3170},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44246041,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"176","issue":null,"first_page":"114626","last_page":"114626"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13038","display_name":"Internet of Things and AI","score":0.04500000178813934,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13038","display_name":"Internet of Things and AI","score":0.04500000178813934,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.042399998754262924,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T14319","display_name":"Currency Recognition and Detection","score":0.0421999990940094,"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/drone","display_name":"Drone","score":0.8352000117301941},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5893999934196472},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5753999948501587},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.546999990940094},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3898000121116638},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.33390000462532043}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8870000243186951},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.8352000117301941},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6959999799728394},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6557999849319458},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5893999934196472},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5753999948501587},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.546999990940094},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3898000121116638},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.33390000462532043},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.32019999623298645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.29899999499320984},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2768999934196472},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.engappai.2026.114626","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114626","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.engappai.2026.114626","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114626","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.5799910426139832}],"awards":[{"id":"https://openalex.org/G1107487223","display_name":null,"funder_award_id":"GuiKe23026264","funder_id":"https://openalex.org/F4320336630","funder_display_name":"Specific Research Project of Guangxi for Research Bases and Talents"},{"id":"https://openalex.org/G2589350968","display_name":null,"funder_award_id":"2024ZY011","funder_id":"https://openalex.org/F4320321106","funder_display_name":"Ministry of Education of the People's Republic of China"},{"id":"https://openalex.org/G708414365","display_name":null,"funder_award_id":"62388101","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"},{"id":"https://openalex.org/F4320321106","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934"},{"id":"https://openalex.org/F4320335669","display_name":"Key Laboratory of System Control and Information Processing","ror":null},{"id":"https://openalex.org/F4320336630","display_name":"Specific Research Project of Guangxi for Research Bases and Talents","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2995199175","https://openalex.org/W2996025707","https://openalex.org/W2996735448","https://openalex.org/W3036271496","https://openalex.org/W3047731328","https://openalex.org/W3116963012"],"related_works":[],"abstract_inverted_index":{"Transformer-based":[0],"methods":[1],"such":[2,34],"as":[3,35],"Detection":[4],"Transformer":[5,62],"(DETR)":[6],"are":[7],"playing":[8],"an":[9,57],"important":[10],"role":[11],"in":[12,19,46,76,102,129,173],"the":[13,47,52,68,100,108,127,141,153,159,162],"field":[14],"of":[15,44,70,99,143,161],"object":[16,22,37,113,130,148,176],"detection.":[17,149,177],"However,":[18],"drone":[20,77,174],"image":[21,175],"detection,":[23],"DETR":[24],"has":[25],"difficulty":[26],"leveraging":[27],"its":[28],"algorithmic":[29],"advantages":[30],"due":[31],"to":[32,51,86,92,125],"issues":[33],"small":[36,71,147],"size,":[38],"large-scale":[39],"changes,":[40],"and":[41,72,106,155],"uneven":[42],"distribution":[43],"objects":[45,75,105],"image.":[48,78],"In":[49],"response":[50],"above":[53],"issues,":[54],"we":[55],"propose":[56],"improved":[58],"noising":[59,81,144],"training":[60,82,121,145],"detection":[61],"(INT-DETR)":[63],"algorithm":[64,122],"aiming":[65],"at":[66],"solving":[67],"problem":[69],"dense":[73,112],"distributed":[74],"Firstly,":[79],"a":[80,116],"module":[83],"is":[84,123],"designed":[85],"randomly":[87],"add":[88],"varying":[89],"noise":[90],"levels":[91],"ground":[93],"truth.":[94],"This":[95,138],"can":[96],"improve":[97],"stability":[98],"model":[101],"matching":[103,119],"complex":[104],"accelerate":[107],"focus":[109],"on":[110,152],"key":[111],"areas.":[114],"Secondly,":[115],"one-to-many":[117],"label":[118],"assignment":[120],"used":[124],"reduce":[126],"uncertainty":[128],"classification":[131],"caused":[132],"by":[133],"high":[134],"density":[135],"or":[136],"occlusion.":[137],"procedure":[139],"increases":[140],"accuracy":[142],"for":[146],"Finally,":[150],"evaluations":[151],"VisDrone2019-DET":[154],"SeaDronesSeeV2":[156],"datasets":[157],"validate":[158],"effectiveness":[160],"proposed":[163],"method.":[164],"Experimental":[165],"results":[166],"demonstrate":[167],"that":[168],"INT-DETR":[169],"achieves":[170],"superior":[171],"performance":[172]},"counts_by_year":[],"updated_date":"2026-06-14T06:11:07.267592","created_date":"2026-04-07T00:00:00"}
