{"id":"https://openalex.org/W4225010644","doi":"https://doi.org/10.1109/tnnls.2022.3165575","title":"Multiple Guidance Network for Industrial Product Surface Inspection With One Labeled Target Sample","display_name":"Multiple Guidance Network for Industrial Product Surface Inspection With One Labeled Target Sample","publication_year":2022,"publication_date":"2022-04-26","ids":{"openalex":"https://openalex.org/W4225010644","doi":"https://doi.org/10.1109/tnnls.2022.3165575","pmid":"https://pubmed.ncbi.nlm.nih.gov/35471880"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3165575","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3165575","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5051129986","display_name":"Jiaming Xu","orcid":"https://orcid.org/0000-0002-0148-1876"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaming Xu","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068679305","display_name":"Yu Liu","orcid":"https://orcid.org/0000-0002-4191-5974"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Liu","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","Research and Development Center of Precision Electronic Manufacturing Technology, Guangzhou Institute of Modern Industrial Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Research and Development Center of Precision Electronic Manufacturing Technology, Guangzhou Institute of Modern Industrial Technology, Guangzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051129986"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":2.0296,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.87488581,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"34","issue":"12","first_page":"10324","last_page":"10333"},"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":0.9991999864578247,"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":0.9991999864578247,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9986000061035156,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9968000054359436,"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":0.715997576713562},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6617721915245056},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5997174978256226},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.593416690826416},{"id":"https://openalex.org/keywords/visual-inspection","display_name":"Visual inspection","score":0.5428453087806702},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5229878425598145},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5197248458862305},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5071699619293213},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4574401378631592},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44367364048957825},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4145335555076599},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13233399391174316},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08847388625144958},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.07873857021331787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.715997576713562},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6617721915245056},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5997174978256226},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.593416690826416},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.5428453087806702},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5229878425598145},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5197248458862305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5071699619293213},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4574401378631592},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44367364048957825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4145335555076599},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13233399391174316},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08847388625144958},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.07873857021331787},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3165575","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3165575","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35471880","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35471880","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5899999737739563}],"awards":[{"id":"https://openalex.org/G2873358808","display_name":null,"funder_award_id":"2020B1515120071","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G5006912042","display_name":null,"funder_award_id":"2021B0101200001","funder_id":"https://openalex.org/F4320336405","funder_display_name":"Special Project for Research and Development in Key areas of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320336405","display_name":"Special Project for Research and Development in Key areas of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1825675169","https://openalex.org/W1901129140","https://openalex.org/W2012496675","https://openalex.org/W2108598243","https://openalex.org/W2162280586","https://openalex.org/W2186094539","https://openalex.org/W2194775991","https://openalex.org/W2611405666","https://openalex.org/W2630837129","https://openalex.org/W2736973763","https://openalex.org/W2770908349","https://openalex.org/W2790914279","https://openalex.org/W2895572611","https://openalex.org/W2904559969","https://openalex.org/W2913074553","https://openalex.org/W2943694032","https://openalex.org/W2945270739","https://openalex.org/W2963078159","https://openalex.org/W2963599420","https://openalex.org/W2964899079","https://openalex.org/W2971322375","https://openalex.org/W2981787211","https://openalex.org/W2983850069","https://openalex.org/W2990230185","https://openalex.org/W3016847592","https://openalex.org/W3033502887","https://openalex.org/W3046014872","https://openalex.org/W3046371026","https://openalex.org/W3047258141","https://openalex.org/W3108189450","https://openalex.org/W3171632293","https://openalex.org/W3176418612","https://openalex.org/W3195872781","https://openalex.org/W3200236763","https://openalex.org/W3204576022","https://openalex.org/W4226027146","https://openalex.org/W6637373629","https://openalex.org/W6638389677","https://openalex.org/W6687483927","https://openalex.org/W6739696289","https://openalex.org/W6756657096","https://openalex.org/W6781819027"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2358755282","https://openalex.org/W2625833328","https://openalex.org/W1533177136","https://openalex.org/W4380994516","https://openalex.org/W2556260348"],"abstract_inverted_index":{"Most":[0],"automatic":[1],"product":[2,173],"surface":[3,174],"inspection":[4,74,175],"methods":[5],"in":[6,20,140],"industry":[7],"are":[8,155],"data-hungry":[9],"and":[10,35,100,129,144],"task-specific.":[11],"It":[12],"is":[13,50,86,125,169],"difficult":[14],"to":[15,23,52,71],"collect":[16],"adequate":[17],"labeled":[18,123,137,178],"samples":[19,31],"practice":[21],"due":[22],"factors":[24],"including":[25],"expensive":[26],"data":[27],"annotation":[28],"cost,":[29],"inadequate":[30],"for":[32,88,127,171],"some":[33],"categories,":[34],"limitations":[36],"on":[37],"the":[38,57,59,73,77,80,94,97,106,111,114,122,130,135,141,166],"initial":[39],"production":[40],"stage.":[41],"In":[42,56],"this":[43],"article,":[44],"a":[45,148],"multiple":[46],"guidance":[47,99,102],"network":[48,107,131],"(MGNet)":[49],"proposed":[51,167],"address":[53],"these":[54],"issues.":[55],"network,":[58],"feature":[60,66],"extraction":[61],"machine":[62],"(FEM)":[63],"produces":[64],"four":[65],"maps":[67],"of":[68,76,91,96,113,151],"different":[69],"functions":[70],"enhance":[72],"ability":[75],"algorithm.":[78],"Also,":[79],"probability":[81],"map":[82],"generation":[83],"(PMG)":[84],"module":[85],"designed":[87],"coarse":[89],"positioning":[90],"objects.":[92],"Moreover,":[93],"structures":[95],"mutual":[98],"historical":[101],"(HG)":[103],"guarantee":[104],"that":[105,165],"can":[108,132],"fully":[109],"utilize":[110],"information":[112],"auxiliary":[115],"dataset.":[116],"Only":[117],"one":[118,177],"support":[119],"sample":[120],"containing":[121],"objects":[124,138],"required":[126],"reference,":[128],"determine":[133],"whether":[134],"same":[136],"exist":[139],"query":[142],"images":[143],"locate":[145],"them.":[146],"For":[147],"comprehensive":[149],"evaluation":[150],"MGNet,":[152],"three":[153,159],"experiments":[154],"carried":[156],"out":[157],"using":[158],"real-world":[160],"datasets.":[161],"Experiment":[162],"results":[163],"verify":[164],"method":[168],"promising":[170],"industrial":[172],"with":[176],"target":[179],"sample.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-26T15:22:09.906841","created_date":"2025-10-10T00:00:00"}