{"id":"https://openalex.org/W4327521115","doi":"https://doi.org/10.1145/3573428.3573667","title":"Target temperature region detection of converter thermal infrared image based on improved YOLOv5s","display_name":"Target temperature region detection of converter thermal infrared image based on improved YOLOv5s","publication_year":2022,"publication_date":"2022-10-21","ids":{"openalex":"https://openalex.org/W4327521115","doi":"https://doi.org/10.1145/3573428.3573667"},"language":"en","primary_location":{"id":"doi:10.1145/3573428.3573667","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573428.3573667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering","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":"https://openalex.org/A5055646330","display_name":"Yu Tong","orcid":null},"institutions":[{"id":"https://openalex.org/I31637741","display_name":"Inner Mongolia University of Science and Technology","ror":"https://ror.org/044rgx723","country_code":"CN","type":"education","lineage":["https://openalex.org/I31637741"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Tong","raw_affiliation_strings":["School of Information Engineering, Inner Mongolia University of Science and Technology, China"],"raw_orcid":"https://orcid.org/0000-0003-1759-5736","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Inner Mongolia University of Science and Technology, China","institution_ids":["https://openalex.org/I31637741"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016124836","display_name":"Ailian Li","orcid":"https://orcid.org/0000-0002-2663-7080"},"institutions":[{"id":"https://openalex.org/I31637741","display_name":"Inner Mongolia University of Science and Technology","ror":"https://ror.org/044rgx723","country_code":"CN","type":"education","lineage":["https://openalex.org/I31637741"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ailian Li","raw_affiliation_strings":["School of Information Engineering, Inner Mongolia University of Science and Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-2663-7080","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Inner Mongolia University of Science and Technology, China","institution_ids":["https://openalex.org/I31637741"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I31637741"],"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":"1343","last_page":"1348"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T11856","display_name":"Thermography and Photoacoustic Techniques","score":0.9757999777793884,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/fuse","display_name":"Fuse (electrical)","score":0.635869026184082},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6206876039505005},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5961702466011047},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5703432559967041},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5479625463485718},{"id":"https://openalex.org/keywords/temperature-measurement","display_name":"Temperature measurement","score":0.5318801999092102},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5012645721435547},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4950508177280426},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4794396460056305},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.466198593378067},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4490807056427002},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.44007208943367004},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.43493491411209106},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.4317344129085541},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3943932056427002},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39357802271842957},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21872380375862122},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18582004308700562},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.13512271642684937},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10123154520988464},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.08521336317062378}],"concepts":[{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.635869026184082},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6206876039505005},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5961702466011047},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5703432559967041},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5479625463485718},{"id":"https://openalex.org/C72293138","wikidata":"https://www.wikidata.org/wiki/Q909741","display_name":"Temperature measurement","level":2,"score":0.5318801999092102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5012645721435547},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4950508177280426},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4794396460056305},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.466198593378067},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4490807056427002},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.44007208943367004},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.43493491411209106},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.4317344129085541},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3943932056427002},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39357802271842957},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21872380375862122},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18582004308700562},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.13512271642684937},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10123154520988464},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.08521336317062378},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3573428.3573667","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573428.3573667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering","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":5,"referenced_works":["https://openalex.org/W2570343428","https://openalex.org/W2884585870","https://openalex.org/W2963150697","https://openalex.org/W2963857746","https://openalex.org/W3034971973"],"related_works":["https://openalex.org/W3000097931","https://openalex.org/W2354322770","https://openalex.org/W4237547500","https://openalex.org/W1570848052","https://openalex.org/W2373192430","https://openalex.org/W4239268388","https://openalex.org/W1537496349","https://openalex.org/W2379407973","https://openalex.org/W4243305035","https://openalex.org/W2125195795"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,9,15,28,37,42,49,52,62,70,73,88,108,113,119,124,131,137,142,147,150,158,161],"difficulty":[3],"of":[4,14,41,65,136,149],"real-time":[5],"temperature":[6,39,58,63,96,171,176],"detection":[7,30,79,125,151],"in":[8,107],"converter":[10,43],"smelting":[11],"process,":[12],"most":[13],"production":[16],"sites":[17],"use":[18],"sub-guns":[19],"for":[20,51],"only":[21],"end":[22],"point":[23],"detection,":[24],"In":[25],"this":[26,66],"paper,":[27],"YOLOv5s-XCB":[29],"algorithm":[31,139,164],"is":[32,105,140,144,153,165],"used":[33,106],"to":[34,55,86,100,111,122,167],"automatically":[35],"extract":[36],"target":[38,78,95,170,175],"area":[40],"thermal":[44],"infrared":[45],"image.":[46],"It":[47],"lays":[48],"foundation":[50],"next":[53],"step":[54],"realize":[56],"automatic":[57],"measurement":[59],"combined":[60],"with":[61],"matrix":[64],"area.":[67],"Based":[68],"on":[69],"YOLOv5s":[71,163],"algorithm,":[72],"research":[74],"adds":[75],"a":[76,82],"small":[77,91,169],"layer":[80,110],"and":[81,93,146,173],"CBAM":[83],"attention":[84],"mechanism":[85],"solve":[87],"problem":[89,159],"that":[90,130,160],"targets":[92],"weak":[94,174],"regions":[97],"are":[98],"difficult":[99,166],"detect.":[101],"The":[102,127],"BiFPN":[103],"structure":[104],"Neck":[109],"fuse":[112],"original":[114,162],"feature":[115],"information":[116],"extracted":[117],"by":[118],"backbone":[120],"network":[121],"enhance":[123],"accuracy.":[126],"results":[128],"show":[129],"average":[132],"mean":[133],"precision":[134],"(mAP)":[135],"improved":[138],"95.8%,":[141],"FPS":[143],"69.5,":[145],"confidence":[148],"frame":[152],"significantly":[154],"improved,":[155],"which":[156],"solves":[157],"detect":[168],"areas":[172],"areas.":[177]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
