{"id":"https://openalex.org/W3014672015","doi":"https://doi.org/10.1109/mce.2019.2959075","title":"<i>Deep Learning for Consumer Devices and Services 4\u2014</i>A Review of Learnable Data Augmentation Strategies for Improved Training of Deep Neural Networks","display_name":"<i>Deep Learning for Consumer Devices and Services 4\u2014</i>A Review of Learnable Data Augmentation Strategies for Improved Training of Deep Neural Networks","publication_year":2020,"publication_date":"2020-04-02","ids":{"openalex":"https://openalex.org/W3014672015","doi":"https://doi.org/10.1109/mce.2019.2959075","mag":"3014672015"},"language":"en","primary_location":{"id":"doi:10.1109/mce.2019.2959075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mce.2019.2959075","pdf_url":null,"source":{"id":"https://openalex.org/S2483040032","display_name":"IEEE Consumer Electronics Magazine","issn_l":"2162-2248","issn":["2162-2248","2162-2256"],"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 Consumer Electronics Magazine","raw_type":"journal-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/A5029996716","display_name":"Joseph Lemley","orcid":"https://orcid.org/0000-0002-0595-2313"},"institutions":[{"id":"https://openalex.org/I188760350","display_name":"Ollscoil na Gaillimhe \u2013 University of Galway","ror":"https://ror.org/03bea9k73","country_code":"IE","type":"education","lineage":["https://openalex.org/I188760350"]}],"countries":["IE"],"is_corresponding":true,"raw_author_name":"Joseph Lemley","raw_affiliation_strings":["National University of Ireland, Galway"],"affiliations":[{"raw_affiliation_string":"National University of Ireland, Galway","institution_ids":["https://openalex.org/I188760350"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066217549","display_name":"Peter Corcoran","orcid":"https://orcid.org/0000-0003-1670-4793"},"institutions":[{"id":"https://openalex.org/I188760350","display_name":"Ollscoil na Gaillimhe \u2013 University of Galway","ror":"https://ror.org/03bea9k73","country_code":"IE","type":"education","lineage":["https://openalex.org/I188760350"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Peter Corcoran","raw_affiliation_strings":["National University of Ireland, Galway"],"affiliations":[{"raw_affiliation_string":"National University of Ireland, Galway","institution_ids":["https://openalex.org/I188760350"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029996716"],"corresponding_institution_ids":["https://openalex.org/I188760350"],"apc_list":null,"apc_paid":null,"fwci":0.7816,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.73506083,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"9","issue":"3","first_page":"55","last_page":"63"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.996999979019165,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.996999979019165,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9965000152587891,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9951000213623047,"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":0.772161602973938},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7271997332572937},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7197252511978149},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.680529773235321},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5989031791687012},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5930574536323547},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5674310326576233},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5551055073738098},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.41518527269363403}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.772161602973938},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7271997332572937},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7197252511978149},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.680529773235321},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5989031791687012},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5930574536323547},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5674310326576233},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5551055073738098},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.41518527269363403},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mce.2019.2959075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mce.2019.2959075","pdf_url":null,"source":{"id":"https://openalex.org/S2483040032","display_name":"IEEE Consumer Electronics Magazine","issn_l":"2162-2248","issn":["2162-2248","2162-2256"],"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 Consumer Electronics Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2130259898","https://openalex.org/W2151554678","https://openalex.org/W2595991490","https://openalex.org/W2604262106","https://openalex.org/W2746314669","https://openalex.org/W2751049198","https://openalex.org/W2751134959","https://openalex.org/W2765407302","https://openalex.org/W2770173563","https://openalex.org/W2775795276","https://openalex.org/W2785885246","https://openalex.org/W2885734829","https://openalex.org/W2890234956","https://openalex.org/W2891021639","https://openalex.org/W2892456951","https://openalex.org/W2906648708","https://openalex.org/W2910327402","https://openalex.org/W2914496424","https://openalex.org/W2947395348","https://openalex.org/W2949736877","https://openalex.org/W2952217990","https://openalex.org/W2962920946","https://openalex.org/W2963468256","https://openalex.org/W2963552443","https://openalex.org/W2964057616","https://openalex.org/W2966177877","https://openalex.org/W3009184501","https://openalex.org/W4293388793","https://openalex.org/W4301183790","https://openalex.org/W6695463398","https://openalex.org/W6743428213","https://openalex.org/W6743928203","https://openalex.org/W6744093492","https://openalex.org/W6745136726","https://openalex.org/W6746638498","https://openalex.org/W6747218270","https://openalex.org/W6762334975","https://openalex.org/W6762619590"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W3032952384","https://openalex.org/W3034302643","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2551249631","https://openalex.org/W3208304128","https://openalex.org/W3000197790"],"abstract_inverted_index":{"Learnable":[0],"data":[1,14,55],"augmentation":[2,35,56],"is":[3,28],"a":[4,7,22,29],"technique":[5],"where":[6],"neural":[8,25],"network":[9],"learns":[10],"to":[11,33],"create":[12],"modified":[13],"samples":[15],"that":[16,36],"improve":[17],"the":[18,42,49],"training":[19],"outcome":[20],"from":[21],"second,":[23],"parallel":[24],"network.":[26],"This":[27],"relatively":[30],"new":[31],"approach":[32],"dataset":[34],"has":[37],"inspired":[38],"many":[39],"variations":[40],"in":[41],"last":[43],"few":[44],"years.":[45],"In":[46],"this":[47],"article":[48],"most":[50],"signficiant":[51],"of":[52],"these":[53],"advanced":[54],"strategies":[57],"are":[58],"summarised":[59],"and":[60],"discussed.":[61]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}