{"id":"https://openalex.org/W3003494558","doi":"https://doi.org/10.1109/icumt48472.2019.8970907","title":"A Perspective of the Noise Removal for Faster Neural Network Training","display_name":"A Perspective of the Noise Removal for Faster Neural Network Training","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W3003494558","doi":"https://doi.org/10.1109/icumt48472.2019.8970907","mag":"3003494558"},"language":"en","primary_location":{"id":"doi:10.1109/icumt48472.2019.8970907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icumt48472.2019.8970907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)","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/A5021013784","display_name":"Martin Rajnoha","orcid":null},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Martin Rajnoha","raw_affiliation_strings":["Brno University of Technology,Department of Telecommunication,Brno,Czech Republic","Department of Telecommunication, Brno University of Technology, Brno, Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brno University of Technology,Department of Telecommunication,Brno,Czech Republic","institution_ids":["https://openalex.org/I60587646"]},{"raw_affiliation_string":"Department of Telecommunication, Brno University of Technology, Brno, Czech Republic","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038999471","display_name":"Vojtech Mikulec","orcid":null},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Vojtech Mikulec","raw_affiliation_strings":["Brno University of Technology,Department of Telecommunication,Brno,Czech Republic","Department of Telecommunication, Brno University of Technology, Brno, Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brno University of Technology,Department of Telecommunication,Brno,Czech Republic","institution_ids":["https://openalex.org/I60587646"]},{"raw_affiliation_string":"Department of Telecommunication, Brno University of Technology, Brno, Czech Republic","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036042625","display_name":"Radim B\u00fcrget","orcid":"https://orcid.org/0000-0003-1849-5390"},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Radim Burget","raw_affiliation_strings":["Brno University of Technology,Department of Telecommunication,Brno,Czech Republic","Department of Telecommunication, Brno University of Technology, Brno, Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brno University of Technology,Department of Telecommunication,Brno,Czech Republic","institution_ids":["https://openalex.org/I60587646"]},{"raw_affiliation_string":"Department of Telecommunication, Brno University of Technology, Brno, Czech Republic","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043123588","display_name":"Jiri Drazil","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102302","display_name":"University Hospital Brno","ror":"https://ror.org/00qq1fp34","country_code":"CZ","type":"healthcare","lineage":["https://openalex.org/I4210102302"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Jiri Drazil","raw_affiliation_strings":["3S.cz, s. r. o,Brno,Czech Republic","3S.cz, s. r. o, Brno, Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"3S.cz, s. r. o,Brno,Czech Republic","institution_ids":["https://openalex.org/I4210102302"]},{"raw_affiliation_string":"3S.cz, s. r. o, Brno, Czech Republic","institution_ids":[]}]}],"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":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18800107,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9995999932289124,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9995999932289124,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9991000294685364,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9987999796867371,"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":0.8157994747161865},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.7327640056610107},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6866728067398071},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.664169192314148},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6551586985588074},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6329625844955444},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6117578148841858},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.580035924911499},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5604074597358704},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5481708645820618},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4558911919593811},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.451445072889328},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44371530413627625},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.42928147315979004},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.427133709192276},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4195908308029175},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4191349744796753},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39376673102378845},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.22424551844596863}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8157994747161865},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7327640056610107},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6866728067398071},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.664169192314148},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6551586985588074},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6329625844955444},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6117578148841858},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.580035924911499},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5604074597358704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5481708645820618},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4558911919593811},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.451445072889328},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44371530413627625},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.42928147315979004},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.427133709192276},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4195908308029175},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4191349744796753},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39376673102378845},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.22424551844596863},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icumt48472.2019.8970907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icumt48472.2019.8970907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1782590233","https://openalex.org/W2112796928","https://openalex.org/W2156163116","https://openalex.org/W2163605009","https://openalex.org/W2766191760","https://openalex.org/W2773984877","https://openalex.org/W2793857571","https://openalex.org/W2809598685","https://openalex.org/W2903158431","https://openalex.org/W2912694846","https://openalex.org/W4255421341","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6746449203","https://openalex.org/W6756615331"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2013643406","https://openalex.org/W2027972911","https://openalex.org/W2157978810","https://openalex.org/W2597809628","https://openalex.org/W3046370962"],"abstract_inverted_index":{"Image":[0],"classification":[1,166],"is":[2,10,140,150],"widely":[3],"used":[4],"within":[5],"image":[6],"processing":[7],"area.":[8],"It":[9],"known":[11],"that":[12,144],"insufficient":[13],"amount":[14,47],"of":[15,23,28,48,73,80,87,104,112,137,167],"data":[16,49,132],"has":[17],"negative":[18],"impact":[19],"on":[20,164],"the":[21,38,43,52,65,81,92,97,102,105,110,154],"training":[22,53,62,93,106,123,146],"neural":[24],"networks":[25],"in":[26,33,37,71,156],"terms":[27],"accuracy,":[29],"convergence":[30],"speed":[31,103],"and":[32,55,76,116,125,148],"some":[34],"cases":[35],"even":[36],"inability":[39],"to":[40,100,120,127,152],"converge.":[41],"On":[42],"other":[44],"hand,":[45],"big":[46],"significantly":[50],"increases":[51],"time":[54,147],"costs":[56],"needed":[57],"for":[58,68],"model":[59],"creation.":[60],"Every":[61],"sample":[63],"contains":[64],"part":[66],"valuable":[67],"decision":[69],"(face":[70],"case":[72],"this":[74,138],"paper)":[75],"noise,":[77],"i.e.":[78],"background":[79],"object.":[82],"This":[83],"paper":[84,139],"introduces":[85],"method":[86,143,161],"iterative":[88],"noise":[89,114],"removal":[90,115],"during":[91],"with":[94,96],"combination":[95,111],"transfer":[98,117],"learning":[99,118],"optimize":[101],"process.":[107],"We":[108],"show":[109],"proposed":[113,142],"leads":[119],"more":[121],"effective":[122],"process":[124,155],"enables":[126],"learn":[128],"also":[129],"from":[130,170],"limited":[131],"sets.":[133],"The":[134,160],"main":[135],"contribution":[136],"a":[141],"reduces":[145],"it":[149],"able":[151],"accelerate":[153],"average":[157],"by":[158],"69%.":[159],"was":[162],"tested":[163],"binary":[165],"two":[168],"persons":[169],"LFW":[171],"database.":[172]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
