{"id":"https://openalex.org/W4310333713","doi":"https://doi.org/10.1109/tnnls.2022.3222044","title":"ReSmooth: Detecting and Utilizing OOD Samples When Training With Data Augmentation","display_name":"ReSmooth: Detecting and Utilizing OOD Samples When Training With Data Augmentation","publication_year":2022,"publication_date":"2022-11-24","ids":{"openalex":"https://openalex.org/W4310333713","doi":"https://doi.org/10.1109/tnnls.2022.3222044","pmid":"https://pubmed.ncbi.nlm.nih.gov/36417730"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3222044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3222044","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2205.12606","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100424705","display_name":"Chenyang Wang","orcid":"https://orcid.org/0000-0002-8706-5354"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyang Wang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-8706-5354","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087165831","display_name":"Junjun Jiang","orcid":"https://orcid.org/0000-0002-5694-505X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjun Jiang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-5694-505X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100683258","display_name":"Xiong Zhou","orcid":"https://orcid.org/0000-0002-0856-6696"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiong Zhou","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-0856-6696","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100654390","display_name":"Xianming Liu","orcid":"https://orcid.org/0000-0002-8857-1785"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianming Liu","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-8857-1785","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.667,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.75933913,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"35","issue":"6","first_page":"7899","last_page":"7910"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.991599977016449,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.991599977016449,"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":0.9915000200271606,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9848999977111816,"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":0.7597402334213257},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.628113865852356},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5205429792404175},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.517379641532898},{"id":"https://openalex.org/keywords/jigsaw","display_name":"Jigsaw","score":0.47230127453804016},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4602884352207184},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4595024585723877},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4357277750968933},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4246125817298889},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3872193396091461},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3724394738674164},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06936389207839966}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7597402334213257},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.628113865852356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5205429792404175},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.517379641532898},{"id":"https://openalex.org/C2779405079","wikidata":"https://www.wikidata.org/wiki/Q356040","display_name":"Jigsaw","level":2,"score":0.47230127453804016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4602884352207184},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4595024585723877},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4357277750968933},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4246125817298889},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3872193396091461},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3724394738674164},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06936389207839966},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2022.3222044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3222044","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2205.12606","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.12606","pdf_url":"https://arxiv.org/pdf/2205.12606","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"text"},{"id":"pmid:36417730","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36417730","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2205.12606","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.12606","pdf_url":"https://arxiv.org/pdf/2205.12606","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2168745299","display_name":null,"funder_award_id":"2022YFC3400404","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6163493852","display_name":"\u9762\u5411\u771f\u5b9e\u76d1\u63a7\u73af\u5883\u7684\u4eba\u8138\u8d85\u5206\u8fa8\u7387\u91cd\u5efa\u6280\u672f\u7814\u7a76","funder_award_id":"61971165","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6297762231","display_name":null,"funder_award_id":"61922027","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W2001610032","https://openalex.org/W2059471177","https://openalex.org/W2108598243","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2321533354","https://openalex.org/W2335728318","https://openalex.org/W2531327146","https://openalex.org/W2622100130","https://openalex.org/W2746314669","https://openalex.org/W2751134959","https://openalex.org/W2785325870","https://openalex.org/W2867167548","https://openalex.org/W2948210185","https://openalex.org/W2952217990","https://openalex.org/W2952361104","https://openalex.org/W2963735582","https://openalex.org/W2964137095","https://openalex.org/W2982103617","https://openalex.org/W2990500698","https://openalex.org/W2994088087","https://openalex.org/W2996108195","https://openalex.org/W3001197829","https://openalex.org/W3007630669","https://openalex.org/W3034185248","https://openalex.org/W3035682985","https://openalex.org/W3042879175","https://openalex.org/W3047916742","https://openalex.org/W3092527263","https://openalex.org/W3092741906","https://openalex.org/W3110446398","https://openalex.org/W3114566572","https://openalex.org/W3118608800","https://openalex.org/W3127929528","https://openalex.org/W3138311278","https://openalex.org/W3155189654","https://openalex.org/W3167594489","https://openalex.org/W3176732771","https://openalex.org/W3177024555","https://openalex.org/W3177326298","https://openalex.org/W3177330184","https://openalex.org/W3205597769","https://openalex.org/W4221055893","https://openalex.org/W4225700112","https://openalex.org/W4239072543","https://openalex.org/W4295727797","https://openalex.org/W4301183982","https://openalex.org/W4312439170","https://openalex.org/W6684191040","https://openalex.org/W6728622933","https://openalex.org/W6738471490","https://openalex.org/W6743428213","https://openalex.org/W6743928203","https://openalex.org/W6747899497","https://openalex.org/W6751647823","https://openalex.org/W6751795773","https://openalex.org/W6752760542","https://openalex.org/W6762161020","https://openalex.org/W6762334975","https://openalex.org/W6762619590","https://openalex.org/W6770979763","https://openalex.org/W6771630921","https://openalex.org/W6773005947","https://openalex.org/W6773116539","https://openalex.org/W6773574937","https://openalex.org/W6781574218","https://openalex.org/W6783597904","https://openalex.org/W6784323503","https://openalex.org/W6788314004","https://openalex.org/W6789034737","https://openalex.org/W6795855770","https://openalex.org/W6802647179"],"related_works":["https://openalex.org/W4313442009","https://openalex.org/W3106062205","https://openalex.org/W3083639670","https://openalex.org/W2291971009","https://openalex.org/W2614642134","https://openalex.org/W3112136298","https://openalex.org/W2352772529","https://openalex.org/W1951652671","https://openalex.org/W1578916557","https://openalex.org/W2142815029"],"abstract_inverted_index":{"Data":[0],"augmentation":[1,35,188],"(DA)":[2],"is":[3,170,203],"a":[4,39,62,82,114],"widely":[5],"used":[6],"technique":[7],"for":[8,27],"enhancing":[9],"the":[10,25,53,89,94,142,165,186],"training":[11,31,116],"of":[12,92,141,168],"deep":[13],"neural":[14],"networks.":[15],"Recent":[16],"DA":[17,154],"techniques":[18],"which":[19],"achieve":[20],"state-of-the-art":[21],"performance":[22,167],"always":[23],"meet":[24],"need":[26],"diversity":[28,41],"in":[29,69],"augmented":[30,46,70,97,144],"samples.":[32,110],"However,":[33],"an":[34],"strategy":[36],"that":[37,64,179],"has":[38],"high":[40],"usually":[42],"introduces":[43],"out-of-distribution":[44],"(OOD)":[45],"samples":[47,50,68,71,98,103,107,121,131,134],"and":[48,72,96,99,108,119,132,195,197],"these":[49,102],"consequently":[51],"impair":[52],"performance.":[54],"To":[55,76],"alleviate":[56],"this":[57],"issue,":[58],"we":[59,79,112,136,147],"propose":[60],"ReSmooth,":[61],"framework":[63,151],"first":[65,80],"detects":[66],"OOD":[67,109,120,133,163],"then":[73],"leverages":[74],"them.":[75,200],"be":[77,182],"specific,":[78],"use":[81,140],"Gaussian":[83],"mixture":[84],"model":[85],"(GMM)":[86],"to":[87,185],"fit":[88],"loss":[90],"distribution":[91],"both":[93],"original":[95],"accordingly":[100],"split":[101],"into":[104],"in-distribution":[105],"(ID)":[106],"Then":[111],"start":[113],"new":[115],"where":[117],"ID":[118,130],"are":[122],"incorporated":[123],"with":[124,152],"different":[125],"smooth":[126],"labels.":[127],"By":[128,157],"treating":[129],"unequally,":[135],"can":[137,181],"make":[138],"better":[139],"diverse":[143],"data.":[145],"Furthermore,":[146],"incorporate":[148],"our":[149],"ReSmooth":[150,180],"negative":[153],"(NDA)":[155],"strategies.":[156],"properly":[158],"handling":[159],"their":[160],"intentionally":[161],"created":[162],"samples,":[164],"classification":[166,176],"NDAs":[169],"largely":[171],"ameliorated.":[172],"Experiments":[173],"on":[174,199],"several":[175],"benchmarks":[177],"show":[178],"easily":[183],"extended":[184],"existing":[187],"strategies":[189],"[such":[190],"as":[191],"RandAugment":[192],"(RA),":[193],"rotate,":[194],"jigsaw]":[196],"improve":[198],"Our":[201],"code":[202],"available":[204],"at":[205],"https://github.com/Chenyang4/ReSmooth.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}
