{"id":"https://openalex.org/W4385301507","doi":"https://doi.org/10.1109/coins57856.2023.10189246","title":"Industrial defect detection on the edge with deep learning over scarcely labeled and extremely imbalanced data","display_name":"Industrial defect detection on the edge with deep learning over scarcely labeled and extremely imbalanced data","publication_year":2023,"publication_date":"2023-07-23","ids":{"openalex":"https://openalex.org/W4385301507","doi":"https://doi.org/10.1109/coins57856.2023.10189246"},"language":"en","primary_location":{"id":"doi:10.1109/coins57856.2023.10189246","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/coins57856.2023.10189246","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://orbilu.uni.lu/handle/10993/54839","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010852800","display_name":"Joe Lorentz","orcid":"https://orcid.org/0000-0003-0786-4488"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Joe Lorentz","raw_affiliation_strings":["DataThings S.A.,Luxembourg,Luxembourg","DataThings S.A., Luxembourg, Luxembourg","SnT, University of Luxembourg, Luxembourg, Luxembourg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DataThings S.A.,Luxembourg,Luxembourg","institution_ids":["https://openalex.org/I186903577"]},{"raw_affiliation_string":"DataThings S.A., Luxembourg, Luxembourg","institution_ids":[]},{"raw_affiliation_string":"SnT, University of Luxembourg, Luxembourg, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010829193","display_name":"Thomas Hartmann","orcid":"https://orcid.org/0000-0002-0465-6280"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Thomas Hartmann","raw_affiliation_strings":["DataThings S.A.,Luxembourg,Luxembourg","DataThings S.A., Luxembourg, Luxembourg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DataThings S.A.,Luxembourg,Luxembourg","institution_ids":["https://openalex.org/I186903577"]},{"raw_affiliation_string":"DataThings S.A., Luxembourg, Luxembourg","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054189204","display_name":"Assaad Moawad","orcid":"https://orcid.org/0000-0002-1561-8992"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Assaad Moawad","raw_affiliation_strings":["DataThings S.A.,Luxembourg,Luxembourg","DataThings S.A., Luxembourg, Luxembourg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DataThings S.A.,Luxembourg,Luxembourg","institution_ids":["https://openalex.org/I186903577"]},{"raw_affiliation_string":"DataThings S.A., Luxembourg, Luxembourg","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083368272","display_name":"Djamila Aouada","orcid":"https://orcid.org/0000-0002-7576-2064"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Djamila Aouada","raw_affiliation_strings":["University of Luxembourg,SnT,Luxembourg,Luxembourg","SnT, University of Luxembourg, Luxembourg, Luxembourg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Luxembourg,SnT,Luxembourg,Luxembourg","institution_ids":["https://openalex.org/I186903577"]},{"raw_affiliation_string":"SnT, University of Luxembourg, Luxembourg, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I186903577"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15512609,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"1","last_page":"6"},"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9901000261306763,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.989799976348877,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"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/computer-science","display_name":"Computer science","score":0.802810549736023},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6895085573196411},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6876072287559509},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6550998687744141},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.6515666246414185},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5661028623580933},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5603036284446716},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5384393334388733},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5338130593299866},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41721513867378235},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07696151733398438}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.802810549736023},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6895085573196411},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6876072287559509},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6550998687744141},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.6515666246414185},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5661028623580933},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5603036284446716},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5384393334388733},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5338130593299866},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41721513867378235},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07696151733398438},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/coins57856.2023.10189246","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/coins57856.2023.10189246","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","raw_type":"proceedings-article"},{"id":"pmh:oai:orbilu.uni.lu:10993/54839","is_oa":true,"landing_page_url":"http://orbilu.uni.lu/handle/10993/54839","pdf_url":null,"source":{"id":"https://openalex.org/S4306401815","display_name":"Open Repository and Bibliography (University of Luxembourg)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I186903577","host_organization_name":"University of Luxembourg","host_organization_lineage":["https://openalex.org/I186903577"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"http://purl.org/coar/resource_type/c_8042"}],"best_oa_location":{"id":"pmh:oai:orbilu.uni.lu:10993/54839","is_oa":true,"landing_page_url":"http://orbilu.uni.lu/handle/10993/54839","pdf_url":null,"source":{"id":"https://openalex.org/S4306401815","display_name":"Open Repository and Bibliography (University of Luxembourg)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I186903577","host_organization_name":"University of Luxembourg","host_organization_lineage":["https://openalex.org/I186903577"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"http://purl.org/coar/resource_type/c_8042"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.550000011920929,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1644641054","https://openalex.org/W2091250708","https://openalex.org/W2117539524","https://openalex.org/W2165698076","https://openalex.org/W2194775991","https://openalex.org/W2786070938","https://openalex.org/W2794550100","https://openalex.org/W2904870462","https://openalex.org/W2907882680","https://openalex.org/W2914154500","https://openalex.org/W2917344403","https://openalex.org/W2936503027","https://openalex.org/W2951970475","https://openalex.org/W2954996726","https://openalex.org/W2963263347","https://openalex.org/W3001197829","https://openalex.org/W3035682985","https://openalex.org/W3042611018","https://openalex.org/W3046289513","https://openalex.org/W3081612852","https://openalex.org/W3118608800","https://openalex.org/W3122855191","https://openalex.org/W3205500251","https://openalex.org/W4312373370","https://openalex.org/W4393805319","https://openalex.org/W6726497184","https://openalex.org/W6759044181","https://openalex.org/W6760000479","https://openalex.org/W6764051988","https://openalex.org/W6773005947","https://openalex.org/W6780353226","https://openalex.org/W6780793664","https://openalex.org/W6782490261","https://openalex.org/W6802864417","https://openalex.org/W6863786681"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Reliable":[0],"automated":[1],"defect":[2,102],"detection":[3,103],"is":[4],"an":[5],"integral":[6],"part":[7],"of":[8,23,49,69,91,122,134],"modern":[9],"manufacturing":[10],"and":[11,45,83,118,125],"improved":[12],"performance":[13],"can":[14],"provide":[15],"a":[16,66,100,115],"competitive":[17],"advantage.":[18],"Despite":[19],"the":[20,40,50,70,89,132],"proven":[21],"capabilities":[22],"convolutional":[24],"neural":[25],"networks":[26],"(CNNs)":[27],"for":[28,43,105],"image":[29],"classification,":[30],"application":[31],"on":[32],"real":[33,92,139],"world":[34,93,140],"tasks":[35],"remains":[36],"challenging":[37,138],"due":[38],"to":[39,59,73,111],"high":[41],"demand":[42],"labeled":[44,124],"well":[46],"balanced":[47],"data":[48,81,113],"common":[51],"supervised":[52],"learning":[53,56],"scheme.":[54],"Semi-supervised":[55],"(SSL)":[57],"promises":[58],"achieve":[60],"comparable":[61],"accuracy":[62],"while":[63],"only":[64],"requiring":[65],"small":[67],"fraction":[68],"training":[71],"samples":[72],"be":[74],"labeled.":[75],"However,":[76],"SSL":[77,135],"methods":[78],"struggle":[79],"with":[80],"imbalance":[82],"existing":[84],"benchmarks":[85],"do":[86],"not":[87],"reflect":[88],"challenges":[90],"applications.":[94],"In":[95],"this":[96,137],"work":[97],"we":[98,130],"present":[99],"CNN-based":[101],"unit":[104],"thermal":[106],"sensors.":[107],"We":[108],"describe":[109],"how":[110],"collect":[112],"from":[114],"running":[116],"process":[117],"release":[119],"our":[120],"dataset":[121],"1k":[123],"293k":[126],"unlabeled":[127],"samples.":[128],"Furthermore,":[129],"investigate":[131],"use":[133],"under":[136],"task.":[141]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
