{"id":"https://openalex.org/W4404740798","doi":"https://doi.org/10.1109/icbase63199.2024.10762006","title":"The Detection of Engineering Vehicle on Remote Sensing Image Using Improved YOLOv5","display_name":"The Detection of Engineering Vehicle on Remote Sensing Image Using Improved YOLOv5","publication_year":2024,"publication_date":"2024-09-20","ids":{"openalex":"https://openalex.org/W4404740798","doi":"https://doi.org/10.1109/icbase63199.2024.10762006"},"language":"en","primary_location":{"id":"doi:10.1109/icbase63199.2024.10762006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbase63199.2024.10762006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Big Data &amp;amp; Artificial Intelligence &amp;amp; Software Engineering (ICBASE)","raw_type":"proceedings-article"},"type":"conference-paper","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":null,"display_name":"Jinwang Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinwang Chen","raw_affiliation_strings":["State Grid Xiamen Electric Power Supply Company,Xiamen,China,361004"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Xiamen Electric Power Supply Company,Xiamen,China,361004","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102222892","display_name":"Shaoxin Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shaoxin Chen","raw_affiliation_strings":["State Grid Xiamen Electric Power Supply Company,Xiamen,China,361004"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Xiamen Electric Power Supply Company,Xiamen,China,361004","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113296577","display_name":"Mingxing Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mingxing Shi","raw_affiliation_strings":["State Grid Xiamen Electric Power Supply Company,Xiamen,China,361004"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Xiamen Electric Power Supply Company,Xiamen,China,361004","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100772114","display_name":"Shu Lin","orcid":"https://orcid.org/0000-0003-1401-7834"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shu Lin","raw_affiliation_strings":["State Grid Xiamen Electric Power Supply Company,Xiamen,China,361004"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Xiamen Electric Power Supply Company,Xiamen,China,361004","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006492100","display_name":"Mengying Huang","orcid":"https://orcid.org/0000-0002-9719-4619"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengying Huang","raw_affiliation_strings":["Fuzhou University,School of Electrical Engineering and Automation,Fuzhou,China,350108"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuzhou University,School of Electrical Engineering and Automation,Fuzhou,China,350108","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100446427","display_name":"Xinyu Liu","orcid":"https://orcid.org/0000-0002-1980-0468"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Liu","raw_affiliation_strings":["Fuzhou University,School of Electrical Engineering and Automation,Fuzhou,China,350108"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuzhou University,School of Electrical Engineering and Automation,Fuzhou,China,350108","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"372","last_page":"377"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.5665000081062317,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.5665000081062317,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6005560159683228},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4964483380317688},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4609203338623047},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4603843688964844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4053765535354614},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1415301263332367}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6005560159683228},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4964483380317688},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4609203338623047},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4603843688964844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4053765535354614},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1415301263332367}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icbase63199.2024.10762006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbase63199.2024.10762006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Big Data &amp;amp; Artificial Intelligence &amp;amp; Software Engineering (ICBASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320317218","display_name":"State Grid Fujian Electric Power Company","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W2102605133","https://openalex.org/W2963037989","https://openalex.org/W3002804910","https://openalex.org/W3174507101","https://openalex.org/W4210465160","https://openalex.org/W4393308750","https://openalex.org/W4399557237","https://openalex.org/W6750227808"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Construction":[0],"vehicles":[1,15,50],"play":[2],"an":[3,36],"important":[4],"role":[5],"on":[6,35],"construction":[7],"sites.":[8],"Real-time":[9],"and":[10,24,59,100,135,159,172],"accurate":[11],"monitoring":[12],"of":[13,48,68,102],"these":[14],"can":[16],"help":[17],"oversee":[18],"site":[19],"activities,":[20],"improve":[21,64],"work":[22],"efficiency,":[23],"enhance":[25,97],"safety.":[26],"A":[27],"novel":[28],"engineering":[29,49,179],"vehicle":[30,180],"object":[31,46],"detection":[32,47,61,66],"algorithm":[33,166],"based":[34],"enhanced":[37,165],"YOLOv5":[38,158],"is":[39,111],"proposed":[40],"since":[41],"the":[42,65,69,76,88,98,103,114,118,126,133,157],"challenges":[43],"faced":[44],"in":[45,51,117,169,178],"remote":[52],"sensing":[53],"images":[54],"such":[55],"as":[56],"complex":[57],"backgrounds":[58],"low":[60],"accuracy.":[62,150],"To":[63],"accuracy":[67,99],"model,":[70],"three":[71],"modules":[72,84,95],"are":[73,85,130],"introduced.":[74],"First,":[75],"Backbone\u2019s":[77],"CSP":[78,89],"Bottleneck":[79,90],"with":[80,87,91,132],"3":[81],"convolutions":[82,93,129],"(C3)":[83],"replaced":[86],"2":[92],"(C2f)":[94],"to":[96,120,156],"robustness":[101],"improved":[104,146],"model.":[105],"Next,":[106],"Global":[107],"Attention":[108],"Mechanism":[109],"(GAM)":[110],"added":[112],"after":[113],"fourth":[115],"C2f":[116],"Backbone":[119],"precisely":[121],"capture":[122],"crucial":[123],"features.":[124],"Finally,":[125],"Neck\u2019s":[127],"fixed":[128],"substituted":[131],"efficient":[134],"lightweight":[136,145],"Group":[137],"Shuffle":[138],"Convolution":[139],"(GSConv),":[140],"which":[141,174],"ensures":[142],"a":[143],"more":[144],"model":[147],"without":[148],"compromising":[149],"Experimental":[151],"results":[152],"demonstrate":[153],"that":[154],"compared":[155],"some":[160],"other":[161],"benchmark":[162],"frameworks,":[163],"our":[164],"shows":[167],"improvements":[168],"precision,":[170],"recall":[171],"F1-score,":[173],"indicates":[175],"superior":[176],"performance":[177],"detection.":[181]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
