{"id":"https://openalex.org/W4389104917","doi":"https://doi.org/10.1109/tie.2023.3329260","title":"Semisupervised Classification With Sequence Gaussian Mixture Variational Autoencoder","display_name":"Semisupervised Classification With Sequence Gaussian Mixture Variational Autoencoder","publication_year":2023,"publication_date":"2023-11-28","ids":{"openalex":"https://openalex.org/W4389104917","doi":"https://doi.org/10.1109/tie.2023.3329260"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2023.3329260","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5101428049","display_name":"Shuangqing Wang","orcid":"https://orcid.org/0000-0003-3057-4518"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangqing Wang","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102732360","display_name":"Jianbo Yu","orcid":"https://orcid.org/0000-0003-4535-7436"},"institutions":[{"id":"https://openalex.org/I4210132426","display_name":"Shanghai Fudan Microelectronics (China)","ror":"https://ror.org/02vfj3j86","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132426"]},{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianbo Yu","raw_affiliation_strings":["School of Microelectronics, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I4210132426","https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100715584","display_name":"Zhi Li","orcid":"https://orcid.org/0000-0001-9057-9623"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Li","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042520521","display_name":"Tianyou Chai","orcid":"https://orcid.org/0000-0002-4623-1483"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyou Chai","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":67},"biblio":{"volume":"71","issue":"9","first_page":"11540","last_page":"11548"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11595","display_name":"Textile materials and evaluations","score":0.9987,"subfield":{"id":"https://openalex.org/subfields/2507","display_name":"Polymers and Plastics"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11595","display_name":"Textile materials and evaluations","score":0.9987,"subfield":{"id":"https://openalex.org/subfields/2507","display_name":"Polymers and Plastics"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.985,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6006203}],"concepts":[{"id":"https://openalex.org/C127937792","wikidata":"https://www.wikidata.org/wiki/Q256069","display_name":"Species evenness","level":3,"score":0.94671774},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.62106544},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6006203},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5899058},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5749584},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5321108},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.47571236},{"id":"https://openalex.org/C2778787235","wikidata":"https://www.wikidata.org/wiki/Q49007","display_name":"Yarn","level":2,"score":0.41764605},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.366255},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29724938},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17053255},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C53565203","wikidata":"https://www.wikidata.org/wiki/Q17146659","display_name":"Species richness","level":2,"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2023.3329260","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61991404"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"62173077"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"62203118"}],"datasets":[],"versions":[],"referenced_works_count":24,"referenced_works":["https://openalex.org/W1806891645","https://openalex.org/W1959608418","https://openalex.org/W2064675550","https://openalex.org/W2099511815","https://openalex.org/W2108501770","https://openalex.org/W2142626357","https://openalex.org/W2151980995","https://openalex.org/W2730106296","https://openalex.org/W2746791238","https://openalex.org/W2807438712","https://openalex.org/W2810347597","https://openalex.org/W2951220176","https://openalex.org/W2987221721","https://openalex.org/W2998594618","https://openalex.org/W3015966228","https://openalex.org/W3092626859","https://openalex.org/W3206279691","https://openalex.org/W3208260947","https://openalex.org/W3213633401","https://openalex.org/W4211054409","https://openalex.org/W4213415961","https://openalex.org/W4223611486","https://openalex.org/W4290725482","https://openalex.org/W4322754779"],"related_works":["https://openalex.org/W4321789545","https://openalex.org/W3013693939","https://openalex.org/W2983573483","https://openalex.org/W2381070915","https://openalex.org/W2379573398","https://openalex.org/W2352481835","https://openalex.org/W2348590503","https://openalex.org/W2085626726","https://openalex.org/W2078851640","https://openalex.org/W1976998962"],"abstract_inverted_index":{"Evenness":[0],"of":[1,13,23,26,35,38,58,100,107,129,155,162],"filament":[2,164],"yarn":[3,122,130],"is":[4,74],"a":[5,65,86,90,94],"crucial":[6],"indicator":[7,34],"that":[8,147],"significantly":[9],"impacts":[10],"the":[11,24,53,80,105,108,119,142,148,159,163],"quality":[12],"downstream":[14],"textile":[15],"products.":[16],"Therefore,":[17],"accurate":[18],"real-time":[19,54],"prediction":[20],"and":[21,56,78,89,113,132],"classification":[22,99],"coefficient":[25],"variation":[27],"(CV)":[28],"value,":[29],"which":[30],"serves":[31],"as":[32],"an":[33,152],"evenness,":[36],"are":[37],"utmost":[39],"importance.":[40],"However,":[41],"current":[42],"detection":[43],"methods":[44],"predominantly":[45],"rely":[46],"on":[47,118],"offline":[48],"evenness":[49,59,123,131],"testing":[50,124],"devices,":[51],"compromising":[52],"capability":[55],"accuracy":[57,153],"detection.":[60],"To":[61,103],"address":[62],"this":[63],"challenge,":[64],"semisupervised":[66,98],"sequence":[67],"Gaussian":[68],"mixture":[69],"variational":[70],"autoencoder":[71],"(VAE)":[72],"model":[73,84,150],"developed":[75],"for":[76],"predicting":[77],"classifying":[79,158],"CV":[81,160],"value.":[82],"This":[83],"combines":[85],"mix":[87],"VAE":[88],"sequence-to-sequence":[91],"structure,":[92],"integrating":[93],"classifier":[95],"to":[96,140],"achieve":[97],"time-series":[101],"data.":[102],"validate":[104],"effectiveness":[106],"proposed":[109,149],"method,":[110],"both":[111],"software":[112],"hardware":[114],"enhancements":[115],"were":[116,137],"implemented":[117],"existing":[120],"capacitance-based":[121],"device,":[125],"enabling":[126],"uninterrupted":[127],"measurement":[128],"length.":[133],"The":[134],"collected":[135],"data":[136],"then":[138],"used":[139],"train":[141],"model.":[143],"Experimental":[144],"results":[145],"demonstrate":[146],"achieves":[151],"rate":[154],"85%":[156],"in":[157],"value":[161],"yarn.":[165]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4389104917","counts_by_year":[],"updated_date":"2025-01-18T05:21:55.640451","created_date":"2023-11-29"}