{"id":"https://openalex.org/W4388692708","doi":"https://doi.org/10.1109/tim.2023.3332939","title":"Few-Shot Industrial Meter Detection Based on Sim-to-Real Domain Adaptation and Category Augmentation","display_name":"Few-Shot Industrial Meter Detection Based on Sim-to-Real Domain Adaptation and Category Augmentation","publication_year":2023,"publication_date":"2023-11-15","ids":{"openalex":"https://openalex.org/W4388692708","doi":"https://doi.org/10.1109/tim.2023.3332939"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3332939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3332939","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/A5071537020","display_name":"Ming Zeng","orcid":"https://orcid.org/0000-0002-4364-7192"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zeng","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-4364-7192","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040273615","display_name":"Shutong Zhong","orcid":"https://orcid.org/0009-0000-8035-8421"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shutong Zhong","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0000-8035-8421","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050381337","display_name":"Leijiao Ge","orcid":"https://orcid.org/0000-0001-6310-6986"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leijiao Ge","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-6310-6986","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.5318,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.67418604,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"73","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9805999994277954,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9805999994277954,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9611999988555908,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9487000107765198,"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/classifier","display_name":"Classifier (UML)","score":0.6860268712043762},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6715723872184753},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6403117179870605},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6036304235458374},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5461836457252502},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.49330607056617737},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.46933144330978394},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4103044271469116},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3575022518634796},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35187721252441406},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18096110224723816}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6860268712043762},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6715723872184753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6403117179870605},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6036304235458374},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5461836457252502},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.49330607056617737},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.46933144330978394},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4103044271469116},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3575022518634796},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35187721252441406},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18096110224723816},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2023.3332939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3332939","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G500695806","display_name":null,"funder_award_id":"2022YFB2403800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1861492603","https://openalex.org/W1966420092","https://openalex.org/W1995875735","https://openalex.org/W2187089797","https://openalex.org/W2193145675","https://openalex.org/W2340897893","https://openalex.org/W2463874335","https://openalex.org/W2552491779","https://openalex.org/W2560536817","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963201472","https://openalex.org/W2964115968","https://openalex.org/W2964241181","https://openalex.org/W2968634921","https://openalex.org/W2979548969","https://openalex.org/W3018757597","https://openalex.org/W3034779842","https://openalex.org/W3034937575","https://openalex.org/W3034971973","https://openalex.org/W3035673985","https://openalex.org/W3088193989","https://openalex.org/W3092609815","https://openalex.org/W3106250896","https://openalex.org/W3110653358","https://openalex.org/W3128861763","https://openalex.org/W3165113810","https://openalex.org/W3184439416","https://openalex.org/W3213148824","https://openalex.org/W4200167257","https://openalex.org/W4287888347","https://openalex.org/W4288325606","https://openalex.org/W4293057111","https://openalex.org/W4293584584","https://openalex.org/W4320002812","https://openalex.org/W6639480849","https://openalex.org/W6679045638","https://openalex.org/W6750227808","https://openalex.org/W6764322716","https://openalex.org/W6777046832","https://openalex.org/W6791353385","https://openalex.org/W6795288823","https://openalex.org/W6797906067","https://openalex.org/W6798838024"],"related_works":["https://openalex.org/W3080655457","https://openalex.org/W4389474468","https://openalex.org/W3166286441","https://openalex.org/W3214142563","https://openalex.org/W3136267388","https://openalex.org/W4287263085","https://openalex.org/W3186065094","https://openalex.org/W3204418343","https://openalex.org/W3093803318","https://openalex.org/W3132602785"],"abstract_inverted_index":{"Rapid":[0],"and":[1,62,140,168,179,200],"accurate":[2],"detection":[3,47,75,126],"of":[4,32,71,101,117,150,217,225],"industrial":[5,35,45,73],"meters":[6],"in":[7,53,76,153,238],"complex":[8,77],"scenarios":[9],"is":[10,23,40],"an":[11],"essential":[12],"step":[13],"toward":[14],"inspection":[15],"robot":[16],"automatic":[17],"meter":[18,36,46,74],"recognition.":[19],"Deep":[20],"learning":[21],"(DL)":[22],"a":[24,122],"promising":[25],"solution.":[26],"However,":[27],"due":[28],"to":[29,43,67,84,113],"the":[30,58,69,90,107,115,138,148,174,190,218,223,226],"lack":[31],"large-scale":[33],"public":[34],"image":[37,59],"datasets,":[38],"it":[39],"very":[41],"difficult":[42],"train":[44],"models":[48],"based":[49,128],"on":[50,129],"DL.":[51],"Therefore,":[52],"this":[54],"article,":[55],"we":[56,80,120],"combine":[57],"generation":[60],"technique":[61,66],"sim-to-real":[63],"domain":[64,92,109,118,123,135,151,157,167,220,228,240],"adaption":[65],"address":[68],"problem":[70],"few-shot":[72],"scenarios.":[78],"Specifically,":[79],"use":[81],"Stable":[82],"Diffusion":[83],"generate":[85],"abundant":[86],"virtual":[87],"samples":[88,103,221],"as":[89,106],"source":[91,166,227],"dataset":[93],"by":[94,197],"inputting":[95],"textual":[96],"prompts.":[97],"A":[98],"small":[99],"number":[100],"real":[102,195],"are":[104],"used":[105],"target":[108,169,219],"dataset.":[110,229],"In":[111],"addition,":[112],"attenuate":[114],"effect":[116],"shift,":[119],"propose":[121],"adaptation":[124,158,241],"object":[125,242],"framework":[127,133,175],"category":[130],"augmentation.":[131],"This":[132],"introduces":[134],"information":[136],"into":[137],"classifier":[139],"combines":[141],"uncertainty":[142],"estimation,":[143],"which":[144,188],"not":[145],"only":[146,194,215],"eliminates":[147],"training":[149],"classifiers":[152],"traditional":[154],"adversarial":[155],"learning-based":[156],"algorithms":[159],"but":[160],"also":[161,233],"facilitates":[162],"feature":[163],"alignment":[164],"between":[165],"domain.":[170],"Experiments":[171],"show":[172],"that":[173],"achieves":[176],"50.8%":[177],"mAP50:95":[178,199],"<inline-formula":[180,201],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[181,202],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[182,203],"<tex-math":[183,204],"notation=\"LaTeX\">$55.0\\%":[184],"F1$":[185,206],"</tex-math></inline-formula>":[186,207],"score,":[187],"outperforms":[189,234],"network":[191],"trained":[192],"with":[193,214,222],"images":[196],"8.3%":[198],"notation=\"LaTeX\">$8.7\\%":[205],"score.":[208],"We":[209],"can":[210],"achieve":[211],"close":[212],"performance":[213],"25%":[216],"help":[224],"Moreover,":[230],"our":[231],"method":[232],"other":[235],"state-of-the-art":[236],"methods":[237],"supervised":[239],"detection.":[243]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
