{"id":"https://openalex.org/W2599192953","doi":"https://doi.org/10.1109/bigcomp.2017.7881693","title":"Controlled dropout: A different approach to using dropout on deep neural network","display_name":"Controlled dropout: A different approach to using dropout on deep neural network","publication_year":2017,"publication_date":"2017-02-01","ids":{"openalex":"https://openalex.org/W2599192953","doi":"https://doi.org/10.1109/bigcomp.2017.7881693","mag":"2599192953"},"language":"en","primary_location":{"id":"doi:10.1109/bigcomp.2017.7881693","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigcomp.2017.7881693","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data and Smart Computing (BigComp)","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/A5049352471","display_name":"Byungsoo Ko","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"ByungSoo Ko","raw_affiliation_strings":["Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102870602","display_name":"Han\u2010Gyu Kim","orcid":"https://orcid.org/0000-0003-2684-1409"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Han-Gyu Kim","raw_affiliation_strings":["Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044545845","display_name":"Kyo-Joong Oh","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyo-Joong Oh","raw_affiliation_strings":["Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015094039","display_name":"Ho\u2010Jin Choi","orcid":"https://orcid.org/0000-0002-3398-9543"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ho-Jin Choi","raw_affiliation_strings":["Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5049352471"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":2.7201,"has_fulltext":false,"cited_by_count":39,"citation_normalized_percentile":{"value":0.92248174,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"358","last_page":"362"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9987000226974487,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9987000226974487,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9944999814033508,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9940999746322632,"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/dropout","display_name":"Dropout (neural networks)","score":0.9755035638809204},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8246628046035767},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.720008134841919},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6470469236373901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.571347177028656},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5205591320991516},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4467756748199463}],"concepts":[{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.9755035638809204},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8246628046035767},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.720008134841919},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6470469236373901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.571347177028656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5205591320991516},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4467756748199463}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigcomp.2017.7881693","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigcomp.2017.7881693","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data and Smart Computing (BigComp)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322091","display_name":"Korea Institute of Science and Technology","ror":"https://ror.org/05kzfa883"},{"id":"https://openalex.org/F4320324161","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1547840952","https://openalex.org/W1598866093","https://openalex.org/W1665214252","https://openalex.org/W1994067712","https://openalex.org/W2095705004","https://openalex.org/W2106479238","https://openalex.org/W2116873850","https://openalex.org/W2141125852","https://openalex.org/W2163605009","https://openalex.org/W2184045248","https://openalex.org/W2213612645","https://openalex.org/W2598388636","https://openalex.org/W2613634265","https://openalex.org/W2919115771","https://openalex.org/W6637242042","https://openalex.org/W6674330103","https://openalex.org/W6684191040","https://openalex.org/W6737658843"],"related_works":["https://openalex.org/W4309224979","https://openalex.org/W3116689448","https://openalex.org/W3128220493","https://openalex.org/W3186840088","https://openalex.org/W4287064118","https://openalex.org/W4210794429","https://openalex.org/W2953328427","https://openalex.org/W2605524926","https://openalex.org/W3186919929","https://openalex.org/W4309605561"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"(DNNs),":[3],"which":[4,69],"show":[5,158],"outstanding":[6],"performance":[7,121],"in":[8,59,82],"various":[9],"areas,":[10],"consume":[11],"considerable":[12],"amounts":[13],"of":[14,33,41,53,150,188],"memory":[15,36,86,118],"and":[16,38,85,117,126,152,186],"time":[17,40,84],"during":[18],"training.":[19],"Our":[20],"research":[21,110],"led":[22],"us":[23,106],"to":[24,71,74,104,107],"propose":[25],"a":[26,45,80],"controlled":[27,65,96,124,162,176],"dropout":[28,66,97,102,125,128,163,177,184],"technique":[29,103],"with":[30],"the":[31,35,50,60,100,114,144,160,171],"potential":[32],"reducing":[34],"space":[37],"training":[39,61,83,115],"DNNs.":[42],"Dropout":[43],"is":[44,129,164,178],"popular":[46],"algorithm":[47],"that":[48,159,175],"solves":[49],"overfitting":[51],"problem":[52],"DNNs":[54],"by":[55,132],"randomly":[56],"dropping":[57],"units":[58,70],"process.":[62],"The":[63,155],"proposed":[64,161],"intentionally":[67],"chooses":[68],"drop":[72],"compared":[73],"conventional":[75],"dropout,":[76],"thereby":[77],"possibly":[78],"facilitating":[79],"reduction":[81],"usage.":[87],"In":[88],"this":[89],"paper,":[90],"we":[91],"focus":[92],"on":[93,138],"validating":[94],"whether":[95],"can":[98],"replace":[99],"traditional":[101,127,168],"enable":[105],"further":[108],"our":[109],"aimed":[111],"at":[112],"improving":[113],"speed":[116],"efficiency.":[119],"A":[120],"comparison":[122],"between":[123],"carried":[130],"out":[131],"implementing":[133],"an":[134,182],"image":[135],"classification":[136],"experiment":[137],"data":[139],"comprising":[140],"handwritten":[141],"digits":[142],"from":[143],"MNIST":[145],"dataset":[146],"(Mixed":[147],"National":[148],"Institute":[149],"Standards":[151],"Technology":[153],"dataset).":[154],"experimental":[156,172],"results":[157],"as":[165,167],"effective":[166],"dropout.":[169],"Furthermore,":[170],"result":[173],"implies":[174],"more":[179],"efficient":[180],"when":[181],"appropriate":[183],"rate":[185],"number":[187],"hidden":[189],"layers":[190],"are":[191],"used.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":7},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
