{"id":"https://openalex.org/W4401387080","doi":"https://doi.org/10.1109/access.2024.3439567","title":"YOLOv7-TID: A Lightweight Network for PCB Intelligent Detection","display_name":"YOLOv7-TID: A Lightweight Network for PCB Intelligent Detection","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4401387080","doi":"https://doi.org/10.1109/access.2024.3439567"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3439567","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3439567","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3439567","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5095748249","display_name":"Shulong Zhuo","orcid":"https://orcid.org/0009-0002-4553-106X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shulong Zhuo","raw_affiliation_strings":["College of Information Engineering, Hainan Vocational University of Science and Technology, Haikou, Hainan, China"],"raw_orcid":"https://orcid.org/0009-0002-4553-106X","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Hainan Vocational University of Science and Technology, Haikou, Hainan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049660596","display_name":"Jinmei Shi","orcid":"https://orcid.org/0000-0002-9021-5464"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinmei Shi","raw_affiliation_strings":["College of Information Engineering, Hainan Vocational University of Science and Technology, Haikou, Hainan, China"],"raw_orcid":"https://orcid.org/0000-0002-9021-5464","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Hainan Vocational University of Science and Technology, Haikou, Hainan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106613373","display_name":"Xiaojian Zhou","orcid":"https://orcid.org/0009-0005-8264-1059"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaojian Zhou","raw_affiliation_strings":["College of Information Engineering, Hainan Vocational University of Science and Technology, Haikou, Hainan, China"],"raw_orcid":"https://orcid.org/0009-0005-8264-1059","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Hainan Vocational University of Science and Technology, Haikou, Hainan, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087139827","display_name":"Jicheng Kan","orcid":"https://orcid.org/0000-0002-1142-4293"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jicheng Kan","raw_affiliation_strings":["College of Information Engineering, Hainan Vocational University of Science and Technology, Haikou, Hainan, China"],"raw_orcid":"https://orcid.org/0000-0002-1142-4293","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Hainan Vocational University of Science and Technology, Haikou, Hainan, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5095748249"],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.9806,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78331416,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"12","issue":null,"first_page":"109957","last_page":"109966"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9983000159263611,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.963100016117096,"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":0.7589751482009888},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5742024183273315},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5708112716674805},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.47888869047164917},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.43855154514312744},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4325942397117615},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4278002977371216},{"id":"https://openalex.org/keywords/printed-circuit-board","display_name":"Printed circuit board","score":0.4166986048221588},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3904293179512024},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1897314190864563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7589751482009888},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5742024183273315},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5708112716674805},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.47888869047164917},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.43855154514312744},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4325942397117615},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4278002977371216},{"id":"https://openalex.org/C120793396","wikidata":"https://www.wikidata.org/wiki/Q173350","display_name":"Printed circuit board","level":2,"score":0.4166986048221588},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3904293179512024},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1897314190864563},{"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3439567","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3439567","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a9d64c8c60924ebeaaf5195eb35f8ddf","is_oa":true,"landing_page_url":"https://doaj.org/article/a9d64c8c60924ebeaaf5195eb35f8ddf","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 109957-109966 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3439567","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3439567","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W3121696187","https://openalex.org/W3129420947","https://openalex.org/W3134389753","https://openalex.org/W3203678539","https://openalex.org/W3207877247","https://openalex.org/W3208154594","https://openalex.org/W4206290629","https://openalex.org/W4213436958","https://openalex.org/W4286560905","https://openalex.org/W4312231279","https://openalex.org/W4312738608","https://openalex.org/W4318484048","https://openalex.org/W4323338462","https://openalex.org/W4327649789","https://openalex.org/W4362471027","https://openalex.org/W4375863227","https://openalex.org/W4377832618","https://openalex.org/W4384205855","https://openalex.org/W4385281247","https://openalex.org/W4388740329","https://openalex.org/W4388807184","https://openalex.org/W4389215987","https://openalex.org/W4393308750","https://openalex.org/W6788034315","https://openalex.org/W6796538260","https://openalex.org/W6802878479"],"related_works":["https://openalex.org/W4252608911","https://openalex.org/W2184913151","https://openalex.org/W2389426768","https://openalex.org/W3147987719","https://openalex.org/W2599361292","https://openalex.org/W2698654916","https://openalex.org/W2907188494","https://openalex.org/W3163908127","https://openalex.org/W2013997577","https://openalex.org/W3088721469"],"abstract_inverted_index":{"The":[0,166,238],"Printed":[1],"Circuit":[2],"Board":[3],"(PCB),":[4],"often":[5],"regarded":[6],"as":[7],"the":[8,11,21,93,98,115,124,133,144,154,162,173,177,188,198,206,220,223,233,250,260,269],"cornerstone":[9],"of":[10,23,112,164,230,252],"electronic":[12,24],"information":[13,105],"industry,":[14],"plays":[15],"a":[16,48,86,227],"pivotal":[17],"role":[18],"in":[19,50],"determining":[20],"quality":[22],"products.":[25],"However,":[26],"traditional":[27],"detection":[28,63,73,200,228],"methods":[29],"struggle":[30],"to":[31,38,47,92,96,102,131,152,181,192,256],"identify":[32],"minuscule":[33],"defects":[34],"on":[35,74,80,157,232],"PCBs":[36],"due":[37],"their":[39],"small":[40,119,203],"surface":[41],"area":[42],"and":[43,109,123,126,140,176,185,196,211,240,246,259,276],"intricate":[44],"layouts,":[45],"leading":[46],"decline":[49],"product":[51],"quality.":[52],"To":[53],"address":[54],"these":[55],"challenges,":[56],"we":[57],"propose":[58],"an":[59],"innovative":[60],"lightweight":[61,207],"intelligent":[62],"algorithm,":[64],"named":[65],"YOLOv7-tiny":[66],"Improved":[67],"Detection":[68],"(YOLOv7-TID).":[69],"For":[70],"precise":[71],"defect":[72,235],"PCBs.":[75],"This":[76,267],"new":[77,224],"model,":[78],"based":[79],"YOLOv7-tiny,":[81,222],"incorporates":[82],"several":[83],"enhancements.":[84],"First,":[85],"parallel":[87],"network":[88,95,175],"module":[89,148,180],"is":[90,121,168,254,263],"added":[91],"neck":[94],"bolster":[97],"backbone":[99],"network\u2019s":[100,136,155,199],"ability":[101],"extract":[103],"feature":[104,134,138],"from":[106],"both":[107],"deep":[108],"shallow":[110,158],"layers":[111],"images.":[113],"Second,":[114],"sampling":[116],"scale":[117],"for":[118,202,273],"targets":[120],"increased,":[122],"FPN":[125],"PAN":[127],"structures":[128],"are":[129,242],"improved":[130],"enhance":[132,197],"extraction":[135,139],"semantic":[137],"localization":[141],"capabilities.":[142],"Additionally,":[143,249],"SimAM":[145],"attention":[146],"mechanism":[147],"should":[149],"be":[150],"introduced":[151],"improve":[153],"focus":[156],"features":[159],"without":[160],"increasing":[161],"number":[163,251],"parameters.":[165],"model":[167,208,225,270],"further":[169],"optimized":[170],"by":[171,186,244,265],"using":[172],"slim-neck":[174],"DWConv":[178],"convolution":[179],"reduce":[182],"its":[183],"weight,":[184],"employing":[187],"NWD":[189],"loss":[190,195],"function":[191],"calculate":[193],"positioning":[194],"capability":[201],"targets.":[204],"Finally,":[205],"undergoes":[209],"pruning":[210],"knowledge":[212],"distillation.":[213],"Experimental":[214],"results":[215],"show":[216],"that,":[217],"compared":[218],"with":[219],"original":[221],"achieves":[226],"accuracy":[229],"96.4%":[231],"PCB":[234],"test":[236],"dataset.":[237],"mAP@0.5":[239],"mAP@0.5:.95":[241],"increased":[243],"6.2%":[245],"6.0%,":[247],"respectively.":[248],"parameters":[253],"reduced":[255],"only":[257],"3.5M,":[258],"computation":[261],"load":[262],"decreased":[264],"23.5%.":[266],"makes":[268],"more":[271],"suitable":[272],"industrial":[274],"applications":[275],"embedded":[277],"development":[278],"systems.":[279]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}