{"id":"https://openalex.org/W2152240655","doi":"https://doi.org/10.1109/ijcnn.2009.5178981","title":"A study of the effect of noise injection on the training of artificial neural networks","display_name":"A study of the effect of noise injection on the training of artificial neural networks","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2152240655","doi":"https://doi.org/10.1109/ijcnn.2009.5178981","mag":"2152240655"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2009.5178981","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178981","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","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/A5042975544","display_name":"Yulei Jiang","orcid":"https://orcid.org/0000-0001-9322-0958"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yulei Jiang","raw_affiliation_strings":["Department of Radiology, University of Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088119779","display_name":"Richard M. Zur","orcid":"https://orcid.org/0000-0002-2040-0146"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Richard M. Zur","raw_affiliation_strings":["Department of Radiology, University of Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048354436","display_name":"Lorenzo L. Pesce","orcid":"https://orcid.org/0000-0002-8015-4653"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lorenzo L. Pesce","raw_affiliation_strings":["Department of Radiology, University of Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024321936","display_name":"Karen Drukker","orcid":"https://orcid.org/0000-0001-6544-3476"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karen Drukker","raw_affiliation_strings":["Department of Radiology, University of Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I40347166"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5042975544"],"corresponding_institution_ids":["https://openalex.org/I40347166"],"apc_list":null,"apc_paid":null,"fwci":1.8143,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.88290813,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1428","last_page":"1432"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"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":0.9991000294685364,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9947999715805054,"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/T11236","display_name":"Control Systems and Identification","score":0.9485999941825867,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/overtraining","display_name":"Overtraining","score":0.8927277326583862},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.8109813332557678},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.7302729487419128},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.602082371711731},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5665919184684753},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5154536366462708},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.49571454524993896},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4582710564136505},{"id":"https://openalex.org/keywords/early-stopping","display_name":"Early stopping","score":0.4112769067287445},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3790081739425659},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09768730401992798},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.06448274850845337}],"concepts":[{"id":"https://openalex.org/C2778534509","wikidata":"https://www.wikidata.org/wiki/Q334310","display_name":"Overtraining","level":3,"score":0.8927277326583862},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.8109813332557678},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7302729487419128},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.602082371711731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5665919184684753},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5154536366462708},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49571454524993896},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4582710564136505},{"id":"https://openalex.org/C5465570","wikidata":"https://www.wikidata.org/wiki/Q5326898","display_name":"Early stopping","level":3,"score":0.4112769067287445},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3790081739425659},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09768730401992798},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.06448274850845337},{"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/C2781054738","wikidata":"https://www.wikidata.org/wiki/Q4813730","display_name":"Athletes","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"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/ijcnn.2009.5178981","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178981","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","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":21,"referenced_works":["https://openalex.org/W1890210640","https://openalex.org/W1963790578","https://openalex.org/W2020506948","https://openalex.org/W2030069582","https://openalex.org/W2045234411","https://openalex.org/W2057853719","https://openalex.org/W2061295593","https://openalex.org/W2069401973","https://openalex.org/W2070665556","https://openalex.org/W2072070946","https://openalex.org/W2072258071","https://openalex.org/W2072293577","https://openalex.org/W2086127902","https://openalex.org/W2089114844","https://openalex.org/W2098874108","https://openalex.org/W2100036049","https://openalex.org/W2105822073","https://openalex.org/W2113115183","https://openalex.org/W2124136621","https://openalex.org/W2157825442","https://openalex.org/W6668588286"],"related_works":["https://openalex.org/W2130825577","https://openalex.org/W2093836487","https://openalex.org/W2065110043","https://openalex.org/W2941308841","https://openalex.org/W4247110202","https://openalex.org/W4232398520","https://openalex.org/W2112842910","https://openalex.org/W2030756250","https://openalex.org/W3094216403","https://openalex.org/W2998817056"],"abstract_inverted_index":{"We":[0,51],"studied":[1],"the":[2,9,14,36],"effect":[3],"of":[4,11,16,35,58],"noise":[5,64],"injection":[6,65],"in":[7,13,21,68],"overcoming":[8,28,69],"problem":[10,30],"overtraining":[12,70],"training":[15,38],"artificial":[17,48],"neural":[18,49],"networks":[19],"(ANNs)":[20],"comparison":[22],"with":[23],"other":[24],"common":[25],"approaches":[26],"for":[27],"this":[29],"such":[31],"as":[32,73],"early":[33,81],"stopping":[34,82],"ANN":[37],"process":[39],"and":[40,56,71,83],"weight":[41,84],"decay":[42],"(which":[43],"is":[44,66,72],"similar":[45],"to":[46],"Bayesian":[47],"networks).":[50],"found":[52],"from":[53],"simulation":[54],"studies":[55,57],"a":[59],"computer-aided":[60],"diagnosis":[61],"application":[62],"that":[63],"effective":[67,74,79],"as,":[75],"or":[76],"even":[77],"more":[78],"than,":[80],"decay.":[85]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":1}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}