{"id":"https://openalex.org/W3015845567","doi":"https://doi.org/10.1109/icassp40776.2020.9053475","title":"Discriminant Generative Adversarial Networks with its Application to Equipment Health Classification","display_name":"Discriminant Generative Adversarial Networks with its Application to Equipment Health Classification","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015845567","doi":"https://doi.org/10.1109/icassp40776.2020.9053475","mag":"3015845567"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053475","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053475","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-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/A5100726971","display_name":"Shuai Zheng","orcid":"https://orcid.org/0000-0001-9006-6318"},"institutions":[{"id":"https://openalex.org/I86725329","display_name":"Hitachi Global Storage Technologies (United States)","ror":"https://ror.org/02q0s1x22","country_code":"US","type":"company","lineage":["https://openalex.org/I86725329"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shuai Zheng","raw_affiliation_strings":["Industrial AI Lab, Hitachi America Ltd, Santa Clara, CA, USA"],"affiliations":[{"raw_affiliation_string":"Industrial AI Lab, Hitachi America Ltd, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I86725329"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103731588","display_name":"Chetan Gupta","orcid":null},"institutions":[{"id":"https://openalex.org/I86725329","display_name":"Hitachi Global Storage Technologies (United States)","ror":"https://ror.org/02q0s1x22","country_code":"US","type":"company","lineage":["https://openalex.org/I86725329"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chetan Gupta","raw_affiliation_strings":["Industrial AI Lab, Hitachi America Ltd, Santa Clara, CA, USA"],"affiliations":[{"raw_affiliation_string":"Industrial AI Lab, Hitachi America Ltd, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I86725329"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100726971"],"corresponding_institution_ids":["https://openalex.org/I86725329"],"apc_list":null,"apc_paid":null,"fwci":0.7356,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.69905392,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3067","last_page":"3071"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10876","display_name":"Fault Detection and Control Systems","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.9944000244140625,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.7352766394615173},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.7068605422973633},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6199241280555725},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.602885901927948},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5969683527946472},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5231044292449951},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4557814300060272},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.4439210295677185},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.44261884689331055},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41322576999664307},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33091598749160767},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3273167014122009}],"concepts":[{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.7352766394615173},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.7068605422973633},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6199241280555725},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.602885901927948},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5969683527946472},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5231044292449951},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4557814300060272},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.4439210295677185},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.44261884689331055},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41322576999664307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33091598749160767},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3273167014122009},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053475","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053475","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W281016700","https://openalex.org/W2013821261","https://openalex.org/W2099471712","https://openalex.org/W2120841219","https://openalex.org/W2125389028","https://openalex.org/W2150796457","https://openalex.org/W2173520492","https://openalex.org/W2415594836","https://openalex.org/W2532523702","https://openalex.org/W2593414223","https://openalex.org/W2617137613","https://openalex.org/W2744067593","https://openalex.org/W2785678896","https://openalex.org/W2789509513","https://openalex.org/W2791006446","https://openalex.org/W2791052411","https://openalex.org/W2884805522","https://openalex.org/W2959613672","https://openalex.org/W2962879692","https://openalex.org/W2963226019","https://openalex.org/W2963684088","https://openalex.org/W2963836885","https://openalex.org/W2977967375","https://openalex.org/W4239389501","https://openalex.org/W4295521014","https://openalex.org/W4320013936","https://openalex.org/W6678815747","https://openalex.org/W6685352114","https://openalex.org/W6718140377","https://openalex.org/W6735913928","https://openalex.org/W6748582592","https://openalex.org/W6748634497","https://openalex.org/W6753904365","https://openalex.org/W6768742838","https://openalex.org/W6779669310"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W3008559849","https://openalex.org/W2371177901"],"abstract_inverted_index":{"In":[0],"equipment":[1,190],"health":[2,39,56,191],"classification,":[3],"machines":[4,36],"in":[5,37,71,81,87,101,109,114,118,156],"normal,":[6],"degradation":[7,82,110],"and":[8,128,148,162],"critical":[9,72,115],"stages":[10,57,89],"are":[11,42,90,123,132,159,166],"classified":[12],"based":[13],"on":[14],"domain":[15],"experts":[16],"KPI":[17,22,76],"(Remaining":[18],"Useful":[19],"Life).":[20],"Higher":[21],"values":[23,77],"indicate":[24],"healthier":[25],"machines.":[26],"GANs":[27,185],"can":[28],"be":[29,59],"used":[30],"to":[31],"generate":[32],"sensor":[33,48,85,99,107],"data":[34,86,100,108,121],"for":[35,44,54,141,189],"different":[38,55,88,93,129,157,163],"stages.":[40],"There":[41],"challenges":[43],"this":[45],"type":[46],"of":[47,179],"generation.":[49],"Firstly,":[50],"the":[51,177],"generated":[52,69,79,142,154,180],"samples":[53,70,80,155],"should":[58],"well":[60],"separated.":[61],"For":[62,97],"example,":[63],"it":[64],"is":[65,104],"not":[66,91,133],"preferred":[67],"that":[68,113,153,172],"stage":[73,103,111],"have":[74],"higher":[75],"than":[78,112],"stage.":[83,116],"Secondly,":[84],"equally":[92],"with":[94],"each":[95],"other.":[96],"instance,":[98],"normal":[102],"more":[105,160],"like":[106],"However,":[117],"existing":[119],"GAN,":[120],"labels":[122],"represented":[124],"using":[125],"one-hot":[126],"vectors":[127],"between-class":[130,146],"distances":[131,165],"explicitly":[134,167],"considered.":[135],"We":[136],"propose":[137],"discriminant":[138,174,183],"GANs,":[139],"where,":[140],"samples,":[143,181],"we":[144],"maximize":[145],"distance":[147],"minimize":[149],"within-class":[150],"distance,":[151],"so":[152],"classes":[158],"separable":[161],"betweenclass":[164],"allowed.":[168],"Empirical":[169],"experiments":[170],"show":[171],"(1)":[173],"regularization":[175],"improves":[176],"quality":[178],"(2)":[182],"regularized":[184],"extract":[186],"efficient":[187],"features":[188],"classification.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}