{"id":"https://openalex.org/W2979730642","doi":"https://doi.org/10.1109/fuzz-ieee.2019.8859022","title":"Fuzzy Deep Stack of Autoencoders for Dealing with Data Uncertainty","display_name":"Fuzzy Deep Stack of Autoencoders for Dealing with Data Uncertainty","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2979730642","doi":"https://doi.org/10.1109/fuzz-ieee.2019.8859022","mag":"2979730642"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2019.8859022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2019.8859022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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/A5043160730","display_name":"Bruno Sielly Jales Costa","orcid":"https://orcid.org/0000-0002-3039-4632"},"institutions":[{"id":"https://openalex.org/I1292974536","display_name":"Ford Motor Company (United States)","ror":"https://ror.org/00g2tkw06","country_code":"US","type":"company","lineage":["https://openalex.org/I1292974536"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Bruno Costa","raw_affiliation_strings":["Ford Greenfield Labs - Palo Alto, Ford Motor Co., Palo Alto, CA"],"affiliations":[{"raw_affiliation_string":"Ford Greenfield Labs - Palo Alto, Ford Motor Co., Palo Alto, CA","institution_ids":["https://openalex.org/I1292974536"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027471861","display_name":"Jinesh Jain","orcid":null},"institutions":[{"id":"https://openalex.org/I1292974536","display_name":"Ford Motor Company (United States)","ror":"https://ror.org/00g2tkw06","country_code":"US","type":"company","lineage":["https://openalex.org/I1292974536"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinesh Jain","raw_affiliation_strings":["Ford Greenfield Labs - Palo Alto, Ford Motor Co., Palo Alto, CA"],"affiliations":[{"raw_affiliation_string":"Ford Greenfield Labs - Palo Alto, Ford Motor Co., Palo Alto, CA","institution_ids":["https://openalex.org/I1292974536"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5043160730"],"corresponding_institution_ids":["https://openalex.org/I1292974536"],"apc_list":null,"apc_paid":null,"fwci":0.4201,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.71518435,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991999864578247,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9990000128746033,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.788284420967102},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6486635208129883},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.6086671948432922},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5581409335136414},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5553711652755737},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.4738783538341522},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47188106179237366},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4702761471271515},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44703614711761475},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44229796528816223},{"id":"https://openalex.org/keywords/neuro-fuzzy","display_name":"Neuro-fuzzy","score":0.43931201100349426},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43368351459503174},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.28350913524627686}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.788284420967102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6486635208129883},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.6086671948432922},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5581409335136414},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5553711652755737},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.4738783538341522},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47188106179237366},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4702761471271515},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44703614711761475},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44229796528816223},{"id":"https://openalex.org/C29470771","wikidata":"https://www.wikidata.org/wiki/Q4165150","display_name":"Neuro-fuzzy","level":4,"score":0.43931201100349426},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43368351459503174},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.28350913524627686},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz-ieee.2019.8859022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2019.8859022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W17525587","https://openalex.org/W582134693","https://openalex.org/W1554427862","https://openalex.org/W1567276288","https://openalex.org/W1570834090","https://openalex.org/W1628268552","https://openalex.org/W1904365287","https://openalex.org/W2013022059","https://openalex.org/W2019207321","https://openalex.org/W2025768430","https://openalex.org/W2042970394","https://openalex.org/W2095705004","https://openalex.org/W2100495367","https://openalex.org/W2100659887","https://openalex.org/W2102409316","https://openalex.org/W2110798204","https://openalex.org/W2112796928","https://openalex.org/W2136922672","https://openalex.org/W2145094598","https://openalex.org/W2147717514","https://openalex.org/W2163922914","https://openalex.org/W2164568552","https://openalex.org/W2181347294","https://openalex.org/W2417420127","https://openalex.org/W2431605385","https://openalex.org/W2465549242","https://openalex.org/W2555210016","https://openalex.org/W2613634265","https://openalex.org/W2951266961","https://openalex.org/W2964059111","https://openalex.org/W2997574889","https://openalex.org/W3120740533","https://openalex.org/W6617145748","https://openalex.org/W6633723191","https://openalex.org/W6640036494","https://openalex.org/W6674330103","https://openalex.org/W6675401909","https://openalex.org/W6676481782","https://openalex.org/W6681096077","https://openalex.org/W6685777803","https://openalex.org/W6737658843","https://openalex.org/W6764214684"],"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":{"This":[0,106],"paper":[1],"addresses":[2],"the":[3,13,52,75,100,103,116,125,137,146,150],"problem":[4],"of":[5,16,22,27,74,91,118,160],"dealing":[6,66,180],"with":[7,67,181],"uncertainty":[8,88],"on":[9,89],"neural":[10,54,161,165],"networks":[11],"for":[12,33,65],"specific":[14],"case":[15],"Autoencoders.":[17],"The":[18,140,167],"recently":[19],"introduced":[20],"concepts":[21],"`Autoencoders'":[23],"and":[24,30,36,44,129,148,174],"`Deep":[25],"Stacks":[26],"Autoencoders'":[28],"(DSAE)":[29],"their":[31],"use":[32],"dimensionality":[34],"reduction":[35],"data":[37,68,101,127],"compression":[38],"problems":[39],"have":[40],"gained":[41],"considerable":[42],"attention":[43],"reached":[45],"very":[46,63,71,172],"promising":[47],"results.":[48],"However,":[49],"similarly":[50],"to":[51,86,102,115,136,145,149,157],"traditional":[53],"networks,":[55],"Autoencoders":[56,92,119],"are":[57,61,171],"deterministic":[58],"structures":[59],"that":[60,120,131],"not":[62],"suitable":[64],"uncertainty,":[69],"a":[70,83,112],"important":[72],"aspect":[73],"real-world":[76],"applications.":[77],"In":[78],"this":[79],"paper,":[80],"we":[81],"propose":[82],"fuzzy":[84,97,113,122],"approach":[85,141],"reduce":[87],"stacks":[90],"by":[93,110],"automatically":[94],"adding":[95,111],"qualitative":[96],"information":[98,135],"about":[99],"input":[104],"layer.":[105],"can":[107,154],"be":[108,155],"accomplished":[109],"layer-0":[114],"stack":[117],"extracts":[121],"knowledge":[123,132],"from":[124],"crisp":[126],"set":[128],"includes":[130],"as":[133],"extra":[134],"network":[138,147],"input.":[139],"is":[142],"completely":[143],"transparent":[144],"user":[151],"and,":[152],"theoretically,":[153],"generalized":[156],"any":[158],"architecture":[159],"network,":[162],"including":[163],"convolutional":[164],"networks.":[166],"results":[168],"presented":[169],"here":[170],"encouraging":[173],"present":[175],"substantial":[176],"improvement,":[177],"especially":[178],"when":[179],"noisy":[182],"data.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
