{"id":"https://openalex.org/W4414538694","doi":"https://doi.org/10.1109/icc52391.2025.11160857","title":"A Heterogeneous Data-Driven Multi-Sensor Collaborative Small Target Detection Method for Road Safety in Bad Weather","display_name":"A Heterogeneous Data-Driven Multi-Sensor Collaborative Small Target Detection Method for Road Safety in Bad Weather","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414538694","doi":"https://doi.org/10.1109/icc52391.2025.11160857"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11160857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11160857","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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/A5101689410","display_name":"Hongjin Wang","orcid":"https://orcid.org/0009-0008-9766-1177"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongjin Wang","raw_affiliation_strings":["College of electrical and information Engineering, Hunan Univeristy,Changsha,China"],"affiliations":[{"raw_affiliation_string":"College of electrical and information Engineering, Hunan Univeristy,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107935916","display_name":"Yukui Fu","orcid":"https://orcid.org/0009-0007-8143-4095"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxuan Fu","raw_affiliation_strings":["College of electrical and information Engineering, Hunan Univeristy,Changsha,China"],"affiliations":[{"raw_affiliation_string":"College of electrical and information Engineering, Hunan Univeristy,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103087252","display_name":"Xu Du","orcid":"https://orcid.org/0009-0004-0131-1588"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Du","raw_affiliation_strings":["College of electrical and information Engineering, Hunan Univeristy,Changsha,China"],"affiliations":[{"raw_affiliation_string":"College of electrical and information Engineering, Hunan Univeristy,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074451730","display_name":"Peng Sun","orcid":"https://orcid.org/0000-0001-8356-1329"},"institutions":[{"id":"https://openalex.org/I4210159968","display_name":"Duke Kunshan University","ror":"https://ror.org/04sr5ys16","country_code":"CN","type":"education","lineage":["https://openalex.org/I170897317","https://openalex.org/I37461747","https://openalex.org/I4210159968"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Sun","raw_affiliation_strings":["Duke Kunshan University,China"],"affiliations":[{"raw_affiliation_string":"Duke Kunshan University,China","institution_ids":["https://openalex.org/I4210159968"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081305539","display_name":"Yunze He","orcid":"https://orcid.org/0000-0002-7081-8225"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunze He","raw_affiliation_strings":["College of electrical and information Engineering, Hunan Univeristy,Changsha,China"],"affiliations":[{"raw_affiliation_string":"College of electrical and information Engineering, Hunan Univeristy,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078126584","display_name":"Zhou Nie","orcid":"https://orcid.org/0000-0001-9864-2965"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zexi Nie","raw_affiliation_strings":["College of electrical and information Engineering, Hunan Univeristy,Changsha,China"],"affiliations":[{"raw_affiliation_string":"College of electrical and information Engineering, Hunan Univeristy,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012195474","display_name":"Azzedine Boukerche","orcid":"https://orcid.org/0000-0002-3851-9938"},"institutions":[{"id":"https://openalex.org/I153718931","display_name":"University of Ottawa","ror":"https://ror.org/03c4mmv16","country_code":"CA","type":"education","lineage":["https://openalex.org/I153718931"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Azzedine Boukerche","raw_affiliation_strings":["University of Ottawa,Canada"],"affiliations":[{"raw_affiliation_string":"University of Ottawa,Canada","institution_ids":["https://openalex.org/I153718931"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101689410"],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34179489,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5078","last_page":"5084"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.8115000128746033,"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"}},"topics":[{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.8115000128746033,"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/fusion","display_name":"Fusion","score":0.5360000133514404},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.48649999499320984},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4699000120162964},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.4668999910354614},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.447299987077713},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.44190001487731934},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40070000290870667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.628600001335144},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5360000133514404},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.48649999499320984},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4699000120162964},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.4668999910354614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4661000072956085},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.447299987077713},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.44190001487731934},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40959998965263367},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40070000290870667},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3935000002384186},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.3889999985694885},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38580000400543213},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3783999979496002},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3662000000476837},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3508000075817108},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2800999879837036},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2556999921798706},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc52391.2025.11160857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11160857","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2412782625","https://openalex.org/W2894249833","https://openalex.org/W2909816247","https://openalex.org/W2928165649","https://openalex.org/W2949708697","https://openalex.org/W3086755561","https://openalex.org/W3112288498","https://openalex.org/W3130463448","https://openalex.org/W3167095230","https://openalex.org/W4224288103","https://openalex.org/W4366374902","https://openalex.org/W4372347372","https://openalex.org/W4384499195","https://openalex.org/W4386076325","https://openalex.org/W4390120014","https://openalex.org/W4391467966","https://openalex.org/W4400073289","https://openalex.org/W6947681574"],"related_works":[],"abstract_inverted_index":{"Autonomous":[0],"driving":[1,20],"(AD)":[2],"systems":[3],"requires":[4],"multisensor":[5],"collaboration":[6],"to":[7,36,62],"address":[8],"challenges":[9],"caused":[10],"by":[11,80],"complex":[12],"weather":[13,38],"scenarios.":[14],"The":[15,67,116,145],"recognition":[16,93,98],"accuracy":[17,69],"of":[18,70,91,147],"autonomous":[19],"system":[21],"based":[22,52],"on":[23,27,53,124],"single":[24],"resource,":[25],"either":[26],"image":[28,92],"only":[29],"or":[30],"Lidar":[31],"only,":[32],"becomes":[33],"unreliable":[34],"due":[35],"untested":[37],"conditions,":[39],"occlusions":[40],"objects,":[41],"and":[42,57,83,95,142,169],"other":[43],"factors.":[44],"This":[45],"paper":[46],"proposes":[47],"a":[48,64,131],"decision-level":[49,149],"fusion":[50,73,103,118,150],"network":[51,61,94,99],"an":[54,58],"improved":[55,59,76],"YOLOV7":[56],"CenterPoint":[60],"build":[63],"multi-sensor-collaboration":[65],"scheme.":[66],"overall":[68],"the":[71,89,102,110,125],"proposed":[72,117,148],"algorithm":[74,104,119,151],"is":[75],"for":[77,113],"small":[78],"targets":[79],"adding":[81],"multi-scale":[82],"multi-stage":[84],"attention":[85],"channel":[86],"modules":[87],"into":[88],"backbones":[90],"point":[96],"cloud":[97],"respectively.":[100],"Moreover,":[101],"introduces":[105],"mixed":[106,129],"distance":[107],"constraints":[108],"as":[109,139],"loss":[111],"function":[112],"overlapping":[114],"targets.":[115],"has":[120],"been":[121],"successfully":[122],"tested":[123],"public":[126],"ONCE":[127],"dataset":[128,133],"with":[130],"self-built":[132],"under":[134],"various":[135],"road":[136],"conditions":[137],"such":[138],"sunny,":[140],"night,":[141],"rainy":[143],"weather.":[144],"mAP":[146],"achieves":[152],"<tex":[153,162],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[154,163],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{8":[155,164],"3.":[156],"5":[157],"\\%}$</tex>":[158,166],"in":[159],"sunny":[160],"daytime,":[161],"0":[165],"during":[167,172],"nighttime":[168],"79.1":[170],"%":[171],"rain":[173],"time.":[174]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
