{"id":"https://openalex.org/W4389159150","doi":"https://doi.org/10.1587/transinf.2023edp7033","title":"Shift Quality Classifier Using Deep Neural Networks on Small Data with Dropout and Semi-Supervised Learning","display_name":"Shift Quality Classifier Using Deep Neural Networks on Small Data with Dropout and Semi-Supervised Learning","publication_year":2023,"publication_date":"2023-11-30","ids":{"openalex":"https://openalex.org/W4389159150","doi":"https://doi.org/10.1587/transinf.2023edp7033"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2023edp7033","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1587/transinf.2023edp7033","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/12/E106.D_2023EDP7033/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/12/E106.D_2023EDP7033/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015036097","display_name":"Takefumi Kawakami","orcid":"https://orcid.org/0000-0003-2379-4598"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takefumi KAWAKAMI","raw_affiliation_strings":["Advanced Development Department, AISIN CORPORATION"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Development Department, AISIN CORPORATION","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055437383","display_name":"Takanori Ide","orcid":"https://orcid.org/0000-0002-6189-0188"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takanori IDE","raw_affiliation_strings":["Advanced Development Department, AISIN CORPORATION"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Development Department, AISIN CORPORATION","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004685164","display_name":"Kunihito Hoki","orcid":"https://orcid.org/0000-0001-7509-9461"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kunihito HOKI","raw_affiliation_strings":["Graduate School of Informatics and Engineering, The University of Electro-Communications"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics and Engineering, The University of Electro-Communications","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113934718","display_name":"Masakazu Muramatsu","orcid":null},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masakazu MURAMATSU","raw_affiliation_strings":["Graduate School of Informatics and Engineering, The University of Electro-Communications"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics and Engineering, The University of Electro-Communications","institution_ids":["https://openalex.org/I20529979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1749598,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"E106.D","issue":"12","first_page":"2078","last_page":"2084"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9815000295639038,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9722999930381775,"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":0.8816626071929932},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.7926826477050781},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6448949575424194},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.635575532913208},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6006914973258972},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5723649859428406},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.5143902897834778},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.49378594756126404},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.4918999671936035},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48896610736846924},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3586059510707855},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3273446559906006},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08675894141197205}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8816626071929932},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.7926826477050781},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6448949575424194},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.635575532913208},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6006914973258972},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5723649859428406},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.5143902897834778},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.49378594756126404},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.4918999671936035},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48896610736846924},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3586059510707855},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3273446559906006},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08675894141197205},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2023edp7033","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1587/transinf.2023edp7033","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/12/E106.D_2023EDP7033/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2023edp7033","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1587/transinf.2023edp7033","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/12/E106.D_2023EDP7033/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4389159150.pdf"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W140965598","https://openalex.org/W818657073","https://openalex.org/W1536391014","https://openalex.org/W1968114652","https://openalex.org/W1983320747","https://openalex.org/W1988997988","https://openalex.org/W2061690068","https://openalex.org/W2095705004","https://openalex.org/W2101210369","https://openalex.org/W2108501770","https://openalex.org/W2111316763","https://openalex.org/W2155893237","https://openalex.org/W2236619711","https://openalex.org/W2519887557","https://openalex.org/W2612042441","https://openalex.org/W2992357811","https://openalex.org/W3094549628","https://openalex.org/W4210997624","https://openalex.org/W4286285633"],"related_works":["https://openalex.org/W3082178636","https://openalex.org/W1521968289","https://openalex.org/W2782041652","https://openalex.org/W2952088488","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W2132466791","https://openalex.org/W3208304128","https://openalex.org/W3000197790"],"abstract_inverted_index":{"In":[0,121],"this":[1],"paper,":[2],"we":[3,151,178],"apply":[4],"two":[5],"methods":[6,130],"in":[7,57],"machine":[8],"learning,":[9,13],"dropout":[10],"and":[11,95,109],"semi-supervised":[12,184],"to":[14,52,72,101],"a":[15,36,115,142,153,180,198],"recently":[16],"proposed":[17,131],"method":[18,154,181],"called":[19],"CSQ-SDL":[20,98],"which":[21,92],"uses":[22,156,183],"deep":[23],"neural":[24],"networks":[25],"for":[26],"evaluating":[27],"shift":[28,76],"quality":[29,77],"from":[30,78],"time-series":[31,80],"measurement":[32,81],"data.":[33],"When":[34],"developing":[35],"new":[37],"Automatic":[38],"Transmission":[39],"(AT),":[40],"calibration":[41],"takes":[42],"place":[43],"where":[44],"many":[45],"parameters":[46,89],"of":[47,83,118,145,164,173],"the":[48,66,75,79,84,88,106,138,162,171,190,195],"AT":[49],"are":[50,90,126],"adjusted":[51],"realize":[53],"pleasant":[54],"driving":[55],"experience":[56],"all":[58,63],"situations":[59],"that":[60,155,182,188],"occur":[61],"on":[62,113],"roads":[64],"around":[65],"world.":[67],"Calibration":[68],"requires":[69],"an":[70],"expert":[71],"visually":[73],"assess":[74],"data":[82,119,124,147,166,175],"experiments":[85],"each":[86],"time":[87,103],"changed,":[91],"is":[93,149,168,176],"iterative":[94],"time-consuming.":[96],"The":[97,129],"was":[99],"developed":[100],"shorten":[102],"consumed":[104],"by":[105],"visual":[107],"assessment,":[108],"its":[110],"effectiveness":[111],"depends":[112],"acquiring":[114],"sufficient":[116],"number":[117,144,163,172],"points.":[120],"practice,":[122],"however,":[123],"amounts":[125],"often":[127],"insufficient.":[128],"here":[132],"can":[133],"handle":[134],"such":[135],"cases.":[136],"For":[137,158],"cases":[139,160],"wherein":[140,161],"only":[141],"small":[143,169],"labeled":[146,165],"points":[148,167],"available,":[150],"propose":[152,179],"dropout.":[157],"those":[159],"but":[170],"unlabeled":[174],"sufficient,":[177],"learning.":[185],"Experiments":[186],"show":[187],"while":[189],"former":[191],"gives":[192],"moderate":[193],"improvement,":[194],"latter":[196],"offers":[197],"significant":[199],"performance":[200],"improvement.":[201]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
