{"id":"https://openalex.org/W4289950759","doi":"https://doi.org/10.1109/tim.2022.3186688","title":"Intelligent Process Monitoring of Laser-Induced Graphene Production With Deep Transfer Learning","display_name":"Intelligent Process Monitoring of Laser-Induced Graphene Production With Deep Transfer Learning","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4289950759","doi":"https://doi.org/10.1109/tim.2022.3186688"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3186688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3186688","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5019003956","display_name":"Min Xia","orcid":"https://orcid.org/0000-0001-8057-9654"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Min Xia","raw_affiliation_strings":["Department of Engineering, Lancaster University, Lancaster, U.K"],"raw_orcid":"https://orcid.org/0000-0001-8057-9654","affiliations":[{"raw_affiliation_string":"Department of Engineering, Lancaster University, Lancaster, U.K","institution_ids":["https://openalex.org/I67415387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044361588","display_name":"Haidong Shao","orcid":"https://orcid.org/0000-0001-7106-0009"},"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":"Haidong Shao","raw_affiliation_strings":["College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-7106-0009","affiliations":[{"raw_affiliation_string":"College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023217527","display_name":"Zheng Qun Huang","orcid":"https://orcid.org/0000-0002-9649-9947"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Huang","raw_affiliation_strings":["Institute of Technological Sciences, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-9649-9947","affiliations":[{"raw_affiliation_string":"Institute of Technological Sciences, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036664174","display_name":"Zhe Zhao","orcid":"https://orcid.org/0000-0001-6131-1775"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Zhao","raw_affiliation_strings":["Institute of Technological Sciences, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-6131-1775","affiliations":[{"raw_affiliation_string":"Institute of Technological Sciences, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038591288","display_name":"Feilong Jiang","orcid":"https://orcid.org/0000-0001-5824-1809"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feilong Jiang","raw_affiliation_strings":["Institute of Technological Sciences, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-5824-1809","affiliations":[{"raw_affiliation_string":"Institute of Technological Sciences, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064167213","display_name":"Yaowu Hu","orcid":"https://orcid.org/0000-0002-2200-9431"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaowu Hu","raw_affiliation_strings":["Institute of Technological Sciences, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-2200-9431","affiliations":[{"raw_affiliation_string":"Institute of Technological Sciences, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.664,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.85120009,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9843999743461609,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9843999743461609,"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/T11451","display_name":"Advanced Machining and Optimization Techniques","score":0.928600013256073,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T13049","display_name":"Surface Roughness and Optical Measurements","score":0.9226999878883362,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/graphene","display_name":"Graphene","score":0.8177745342254639},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6155948638916016},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.598468005657196},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5811735391616821},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5389325022697449},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.4519765079021454},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4422640800476074},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4350045323371887},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.42696383595466614},{"id":"https://openalex.org/keywords/nanotechnology","display_name":"Nanotechnology","score":0.25085559487342834}],"concepts":[{"id":"https://openalex.org/C30080830","wikidata":"https://www.wikidata.org/wiki/Q169917","display_name":"Graphene","level":2,"score":0.8177745342254639},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6155948638916016},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.598468005657196},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5811735391616821},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5389325022697449},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.4519765079021454},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4422640800476074},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4350045323371887},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42696383595466614},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.25085559487342834},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tim.2022.3186688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3186688","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:eprints.lancs.ac.uk:175382","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401916","display_name":"Lancaster EPrints (Lancaster University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67415387","host_organization_name":"Lancaster University","host_organization_lineage":["https://openalex.org/I67415387"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1774207900","display_name":null,"funder_award_id":"51905160","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3262465829","display_name":null,"funder_award_id":"51901162","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2003408860","https://openalex.org/W2045912757","https://openalex.org/W2051272760","https://openalex.org/W2070042441","https://openalex.org/W2161187802","https://openalex.org/W2165334178","https://openalex.org/W2165991108","https://openalex.org/W2214432672","https://openalex.org/W2263247421","https://openalex.org/W2311648075","https://openalex.org/W2327192883","https://openalex.org/W2883049074","https://openalex.org/W2949990560","https://openalex.org/W2956231845","https://openalex.org/W2966213627","https://openalex.org/W2970145156","https://openalex.org/W2990456352","https://openalex.org/W3009693422","https://openalex.org/W3027429685","https://openalex.org/W3027744663","https://openalex.org/W3028101274","https://openalex.org/W3037845248","https://openalex.org/W3088105316","https://openalex.org/W3138874558","https://openalex.org/W3199793489"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3183901164","https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W2951211570","https://openalex.org/W3192840557","https://openalex.org/W3167935049"],"abstract_inverted_index":{"Three-dimensional":[0],"graphene":[1,16,26,29],"has":[2],"been":[3],"increasingly":[4],"used":[5],"in":[6,44],"many":[7],"applications":[8],"due":[9],"to":[10,23,92,106],"its":[11],"superior":[12],"properties.":[13],"The":[14,98,126],"laser-induced":[15],"(LIG)":[17],"technique":[18],"is":[19,90],"an":[20],"effective":[21],"way":[22],"produce":[24],"3-D":[25,58],"by":[27],"combining":[28],"preparation":[30],"and":[31,47,54,65,141],"patterning":[32],"into":[33],"a":[34,63,107,119],"single":[35],"step":[36],"using":[37],"direct":[38],"laser":[39],"writing.":[40],"However,":[41],"the":[42,52,77,94,131,136,145,148],"variation":[43],"process":[45],"parameters":[46],"environment":[48],"could":[49],"largely":[50],"affect":[51],"formation":[53],"crystallization":[55],"quality":[56,146],"of":[57,79,123,139,147],"graphene.":[59],"This":[60],"article":[61],"develops":[62],"vision":[64],"deep":[66,110],"transfer":[67],"learning-based":[68],"processing":[69],"monitoring":[70,143],"system":[71],"for":[72,115,144],"LIG":[73,149],"production.":[74],"To":[75],"solve":[76],"problem":[78],"limited":[80],"labeled":[81,124],"data,":[82],"novel":[83],"convolutional":[84,109],"de-noising":[85],"auto-encoder":[86],"(CDAE)-based":[87],"unsupervised":[88],"learning":[89],"developed":[91],"utilize":[93],"available":[95],"unlabeled":[96],"images.":[97,125],"learned":[99],"weights":[100],"from":[101],"CDAE":[102],"are":[103],"then":[104],"transferred":[105],"Gaussian":[108],"belief":[111],"network":[112],"(GCDBN)":[113],"model":[114],"further":[116],"fine-tuning":[117],"with":[118],"very":[120],"small":[121],"amount":[122],"experimental":[127],"results":[128],"show":[129],"that":[130],"proposed":[132],"method":[133],"can":[134],"achieve":[135],"state-of-art":[137],"performance":[138],"precise":[140],"robust":[142],"formation.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
