{"id":"https://openalex.org/W4390993884","doi":"https://doi.org/10.1145/3630138.3630450","title":"Fusion of YOLOv5s and Swin Transformer for forest fire detection","display_name":"Fusion of YOLOv5s and Swin Transformer for forest fire detection","publication_year":2023,"publication_date":"2023-09-24","ids":{"openalex":"https://openalex.org/W4390993884","doi":"https://doi.org/10.1145/3630138.3630450"},"language":"en","primary_location":{"id":"doi:10.1145/3630138.3630450","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3630138.3630450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Power Communication Computing and Networking Technologies","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/A5023967695","display_name":"He Wang","orcid":"https://orcid.org/0000-0002-8086-1964"},"institutions":[{"id":"https://openalex.org/I1300757298","display_name":"Heilongjiang University of Science and Technology","ror":"https://ror.org/030xwyx96","country_code":"CN","type":"education","lineage":["https://openalex.org/I1300757298"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"He Wang","raw_affiliation_strings":["Institute of Electronic and Information Engineering, Heilongjiang University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"Institute of Electronic and Information Engineering, Heilongjiang University of Science and Technology, China","institution_ids":["https://openalex.org/I1300757298"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066712727","display_name":"Huang Yao-qun","orcid":"https://orcid.org/0000-0002-8427-6842"},"institutions":[{"id":"https://openalex.org/I1300757298","display_name":"Heilongjiang University of Science and Technology","ror":"https://ror.org/030xwyx96","country_code":"CN","type":"education","lineage":["https://openalex.org/I1300757298"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaoqun Huang","raw_affiliation_strings":["Institute of Electronic and Information Engineering, Heilongjiang University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"Institute of Electronic and Information Engineering, Heilongjiang University of Science and Technology, China","institution_ids":["https://openalex.org/I1300757298"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101761340","display_name":"Fengxia Zhang","orcid":"https://orcid.org/0009-0001-2854-6887"},"institutions":[{"id":"https://openalex.org/I1300757298","display_name":"Heilongjiang University of Science and Technology","ror":"https://ror.org/030xwyx96","country_code":"CN","type":"education","lineage":["https://openalex.org/I1300757298"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengxia Zhang","raw_affiliation_strings":["Institute of Electronic and Information Engineering, Heilongjiang University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"Institute of Electronic and Information Engineering, Heilongjiang University of Science and Technology, China","institution_ids":["https://openalex.org/I1300757298"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5023967695"],"corresponding_institution_ids":["https://openalex.org/I1300757298"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25070668,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9998000264167786,"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":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9965000152587891,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9900000095367432,"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/computer-science","display_name":"Computer science","score":0.7315109372138977},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6553077697753906},{"id":"https://openalex.org/keywords/fire-detection","display_name":"Fire detection","score":0.6190712451934814},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5793999433517456},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5730660557746887},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5410105586051941},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5221043825149536},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5173115730285645},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4588308036327362},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.45823317766189575},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38634419441223145},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.19910690188407898},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15744251012802124},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.154445618391037}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7315109372138977},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6553077697753906},{"id":"https://openalex.org/C2780836893","wikidata":"https://www.wikidata.org/wiki/Q19922674","display_name":"Fire detection","level":2,"score":0.6190712451934814},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5793999433517456},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5730660557746887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5410105586051941},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5221043825149536},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5173115730285645},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4588308036327362},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.45823317766189575},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38634419441223145},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.19910690188407898},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15744251012802124},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.154445618391037},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3630138.3630450","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3630138.3630450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Power Communication Computing and Networking Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1981276685","https://openalex.org/W2068730032","https://openalex.org/W2102605133","https://openalex.org/W2109255472","https://openalex.org/W2146926380","https://openalex.org/W2565639579","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963873508","https://openalex.org/W3091882159","https://openalex.org/W3138516171","https://openalex.org/W6604218873","https://openalex.org/W6609689914"],"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":{"A":[0],"fire":[1,22,118,205,231,241],"detection":[2,23,28,36,91,176,179,206,232,237,242],"method":[3,46,192,238],"based":[4],"on":[5,50],"YOLOv5s":[6],"fused":[7,108],"with":[8],"Swin":[9,99],"Transformer":[10,55,100],"is":[11,14,124,139,209,218],"proposed.":[12],"This":[13],"to":[15,111,126,145,156,220,224,228],"address":[16],"the":[17,51,54,59,62,81,98,112,128,133,142,147,189,203,215,225],"shortcomings":[18,60],"of":[19,37,53,61,69,92,116,181,200],"traditional":[20],"forest":[21,38,117,204,240],"methods":[24],"such":[25,66,88,173],"as":[26,67,89,153,155,174],"poor":[27,90,178],"accuracy":[29,180],"and":[30,71,101,109,132,159,169,177,214],"low":[31],"reliability.":[32],"To":[33],"achieve":[34,196],"real-time":[35,230],"fires,":[39],"this":[40,96],"paper":[41],"proposes":[42],"an":[43,197,235],"improved":[44,190],"recognition":[45,191],"for":[47,165,239],"YOLOv5s-SwinT.":[48],"Based":[49],"application":[52],"model,":[56],"it":[57],"solves":[58],"convolutional":[63,103],"neural":[64,104],"network":[65,105,144],"localization":[68],"operation":[70],"global":[72],"feature":[73,150],"extraction.":[74],"It":[75],"achieves":[76],"favorable":[77],"results,":[78],"but":[79],"at":[80],"same":[82],"time,":[83],"there":[84],"are":[85,107],"still":[86],"disadvantages":[87],"small":[93,182],"targets.":[94,183],"In":[95],"paper,":[97],"YOLOv5":[102],"models":[106],"applied":[110],"machine":[113],"vision":[114,243],"task":[115],"detection.":[119],"The":[120,184],"\u03b1-IoU":[121],"loss":[122,130],"function":[123],"introduced":[125],"replace":[127],"GIOU":[129],"function,":[131],"CA":[134],"attention":[135],"mechanism":[136],"lightweight":[137],"module":[138],"incorporated":[140],"into":[141],"backbone":[143],"improve":[146],"overall":[148],"network's":[149],"extraction":[151],"capability":[152],"well":[154],"obtain":[157],"high-quality":[158],"highly":[160],"accurate":[161],"localized":[162],"image":[163],"regions":[164],"bounding":[166],"box":[167],"generation":[168],"prediction,":[170],"improving":[171],"problems":[172],"missed":[175],"experimental":[185],"results":[186],"show":[187],"that":[188],"incorporating":[193],"YOLOv5s-SwinT":[194],"can":[195],"mAP":[198],"value":[199],"74.2%":[201],"in":[202],"task,":[207],"which":[208],"4.5%":[210],"higher":[211],"than":[212],"YOLOv5s,":[213],"GUI":[216],"interface":[217],"designed":[219],"be":[221],"deployed":[222],"directly":[223],"PC":[226],"side":[227],"realize":[229],"requirements,":[233],"providing":[234],"effective":[236],"tasks.":[244]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
