{"id":"https://openalex.org/W2997683605","doi":"https://doi.org/10.1109/hsi47298.2019.8942622","title":"The Impact of Architecture on the Deep Neural Networks Training","display_name":"The Impact of Architecture on the Deep Neural Networks Training","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2997683605","doi":"https://doi.org/10.1109/hsi47298.2019.8942622","mag":"2997683605"},"language":"en","primary_location":{"id":"doi:10.1109/hsi47298.2019.8942622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hsi47298.2019.8942622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 12th International Conference on Human System Interaction (HSI)","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/A5020254867","display_name":"Pawe\u0142 R\u00f3\u017cycki","orcid":"https://orcid.org/0000-0002-7519-0203"},"institutions":[{"id":"https://openalex.org/I4210109085","display_name":"University of Information Technology and Management in Rzeszow","ror":"https://ror.org/01t81sv44","country_code":"PL","type":"education","lineage":["https://openalex.org/I4210109085"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Pawel Rozycki","raw_affiliation_strings":["Department of Electronics and Telecommunications, University of Information Technology and Management, Rzeszow, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunications, University of Information Technology and Management, Rzeszow, Poland","institution_ids":["https://openalex.org/I4210109085"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087188240","display_name":"Janusz Kolbusz","orcid":"https://orcid.org/0000-0002-9186-7050"},"institutions":[{"id":"https://openalex.org/I4210109085","display_name":"University of Information Technology and Management in Rzeszow","ror":"https://ror.org/01t81sv44","country_code":"PL","type":"education","lineage":["https://openalex.org/I4210109085"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Janusz Kolbusz","raw_affiliation_strings":["Department of Electronics and Telecommunications, University of Information Technology and Management, Rzeszow, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunications, University of Information Technology and Management, Rzeszow, Poland","institution_ids":["https://openalex.org/I4210109085"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060342311","display_name":"A. Malinowski","orcid":"https://orcid.org/0000-0001-7010-5738"},"institutions":[{"id":"https://openalex.org/I24648388","display_name":"Bradley University","ror":"https://ror.org/04kmeaw70","country_code":"US","type":"education","lineage":["https://openalex.org/I24648388"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aleksander Malinowski","raw_affiliation_strings":["Electrical and Computer Engineering, Bradley University, Peoria, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, Bradley University, Peoria, USA","institution_ids":["https://openalex.org/I24648388"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084622054","display_name":"Bogdan M. Wilamowski","orcid":null},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bogdan Wilamowski","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Auburn University, Auburn, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Auburn University, Auburn, USA","institution_ids":["https://openalex.org/I82497590"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2892,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.68511046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"41","last_page":"46"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","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/T10320","display_name":"Neural Networks and Applications","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/T14319","display_name":"Currency Recognition and Detection","score":0.9836999773979187,"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/T12564","display_name":"Sensor Technology and Measurement Systems","score":0.9715999960899353,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/artificial-neural-network","display_name":"Artificial neural network","score":0.7776153087615967},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.7626502513885498},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.7325923442840576},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7265991568565369},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6460983157157898},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.6354036331176758},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5573049187660217},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49416425824165344},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.41937345266342163},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4126265347003937},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.14456450939178467}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7776153087615967},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.7626502513885498},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.7325923442840576},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7265991568565369},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6460983157157898},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.6354036331176758},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5573049187660217},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49416425824165344},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.41937345266342163},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4126265347003937},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.14456450939178467},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hsi47298.2019.8942622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hsi47298.2019.8942622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 12th International Conference on Human System Interaction (HSI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1665214252","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1932847118","https://openalex.org/W1964155876","https://openalex.org/W1971014294","https://openalex.org/W1973445088","https://openalex.org/W2019282798","https://openalex.org/W2054633808","https://openalex.org/W2065060269","https://openalex.org/W2069143585","https://openalex.org/W2072128103","https://openalex.org/W2076063813","https://openalex.org/W2102013737","https://openalex.org/W2107878631","https://openalex.org/W2111072639","https://openalex.org/W2112796928","https://openalex.org/W2121029939","https://openalex.org/W2125818553","https://openalex.org/W2138857742","https://openalex.org/W2139212933","https://openalex.org/W2145339207","https://openalex.org/W2163605009","https://openalex.org/W2168894214","https://openalex.org/W2170000506","https://openalex.org/W2194775991","https://openalex.org/W2257979135","https://openalex.org/W2325217181","https://openalex.org/W2469702829","https://openalex.org/W2510676265","https://openalex.org/W2907748920","https://openalex.org/W2919115771","https://openalex.org/W4231109964","https://openalex.org/W4239510810","https://openalex.org/W6631943919","https://openalex.org/W6637242042","https://openalex.org/W6638667902","https://openalex.org/W6680300913"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W2979433843","https://openalex.org/W3208304128"],"abstract_inverted_index":{"Deep":[0],"neural":[1,30,69],"networks":[2,31],"are":[3,32,89],"able":[4],"to":[5,34,37],"solve":[6],"much":[7],"more":[8],"complex":[9],"and":[10,41,76,87],"nonlinear":[11],"problems":[12,38,53],"than":[13],"very":[14],"popular":[15],"but":[16],"shallow":[17],"technologies":[18],"such":[19,83],"as":[20,84],"ELM,":[21],"SVR":[22],"or":[23],"SLP.":[24],"Despite":[25],"of":[26,67,94,100,105],"their":[27],"power":[28],"deep":[29],"difficult":[33],"apply":[35],"due":[36],"with":[39],"effective":[40],"successful":[42],"training":[43,74,78],"caused":[44],"by":[45,57],"`vanishing'":[46],"problem.":[47],"The":[48,62],"paper":[49,63],"shows":[50],"that":[51],"these":[52],"can":[54],"be":[55],"reduced":[56],"using":[58],"appropriate":[59],"network":[60,70,81,106],"architecture.":[61],"presents":[64],"the":[65,68,73,77,97,103],"influence":[66,99],"architecture":[71,101],"on":[72,102],"effectiveness":[75],"time.":[79],"Selected":[80],"architectures":[82],"BMPL,":[85],"FCC":[86],"MLPL":[88],"described.":[90],"Presented":[91],"experimental":[92],"results":[93],"research":[95],"confirming":[96],"significant":[98],"success":[104],"training.":[107]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
