{"id":"https://openalex.org/W2978009565","doi":"https://doi.org/10.1109/ijcnn.2019.8852064","title":"Dealing with Limited Access to Data: Comparison of Deep Learning Approaches","display_name":"Dealing with Limited Access to Data: Comparison of Deep Learning Approaches","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978009565","doi":"https://doi.org/10.1109/ijcnn.2019.8852064","mag":"2978009565"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852064","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852064","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","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/A5042671881","display_name":"Andreas Look","orcid":"https://orcid.org/0000-0002-7423-4091"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Andreas Look","raw_affiliation_strings":["IHS, University of Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"IHS, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071670292","display_name":"Stefan Riedelbauch","orcid":"https://orcid.org/0000-0002-3734-8487"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Riedelbauch","raw_affiliation_strings":["IHS, University of Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"IHS, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5042671881"],"corresponding_institution_ids":["https://openalex.org/I100066346"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11582418,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"29","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991000294685364,"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/T11512","display_name":"Anomaly Detection Techniques 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/T12357","display_name":"Digital Media Forensic Detection","score":0.9980000257492065,"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/T11309","display_name":"Music and Audio Processing","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.8248090744018555},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.7315890789031982},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6342462301254272},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.629555344581604},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6224182844161987},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6012247800827026},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5969630479812622},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4699093699455261},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4540444612503052},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43030819296836853},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4276326894760132},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.41765716671943665},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39674222469329834},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08292201161384583}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8248090744018555},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7315890789031982},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6342462301254272},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.629555344581604},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6224182844161987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6012247800827026},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5969630479812622},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4699093699455261},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4540444612503052},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43030819296836853},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4276326894760132},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.41765716671943665},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39674222469329834},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08292201161384583},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852064","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852064","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","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":81,"referenced_works":["https://openalex.org/W630242894","https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W1945616565","https://openalex.org/W2004915807","https://openalex.org/W2038484192","https://openalex.org/W2095705004","https://openalex.org/W2099471712","https://openalex.org/W2108501770","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2127589108","https://openalex.org/W2145494108","https://openalex.org/W2149933564","https://openalex.org/W2191779130","https://openalex.org/W2293363371","https://openalex.org/W2335728318","https://openalex.org/W2401823607","https://openalex.org/W2412510955","https://openalex.org/W2431080869","https://openalex.org/W2509065397","https://openalex.org/W2530816535","https://openalex.org/W2588150943","https://openalex.org/W2592691248","https://openalex.org/W2593768305","https://openalex.org/W2601450892","https://openalex.org/W2616180702","https://openalex.org/W2619371851","https://openalex.org/W2786559811","https://openalex.org/W2799032899","https://openalex.org/W2887603965","https://openalex.org/W2899771611","https://openalex.org/W2949416428","https://openalex.org/W2951970475","https://openalex.org/W2953070460","https://openalex.org/W2962970380","https://openalex.org/W2962972504","https://openalex.org/W2963170156","https://openalex.org/W2963207607","https://openalex.org/W2963250052","https://openalex.org/W2963341924","https://openalex.org/W2963373786","https://openalex.org/W2963435192","https://openalex.org/W2963684088","https://openalex.org/W2964121744","https://openalex.org/W2964159205","https://openalex.org/W3091905774","https://openalex.org/W3098357269","https://openalex.org/W3118608800","https://openalex.org/W3136198447","https://openalex.org/W4239072543","https://openalex.org/W4299518610","https://openalex.org/W4320013936","https://openalex.org/W6619990258","https://openalex.org/W6631190155","https://openalex.org/W6640425456","https://openalex.org/W6674330103","https://openalex.org/W6675944832","https://openalex.org/W6676297131","https://openalex.org/W6681588610","https://openalex.org/W6682132143","https://openalex.org/W6685352114","https://openalex.org/W6685777725","https://openalex.org/W6697274609","https://openalex.org/W6703116779","https://openalex.org/W6713057566","https://openalex.org/W6715189028","https://openalex.org/W6717697761","https://openalex.org/W6717772578","https://openalex.org/W6718379498","https://openalex.org/W6733814495","https://openalex.org/W6735236233","https://openalex.org/W6736346607","https://openalex.org/W6738597727","https://openalex.org/W6748312029","https://openalex.org/W6750707585","https://openalex.org/W6756040250","https://openalex.org/W6764051988","https://openalex.org/W6783596713","https://openalex.org/W6787972765","https://openalex.org/W6791883635"],"related_works":["https://openalex.org/W2950183588","https://openalex.org/W3080754722","https://openalex.org/W4383221314","https://openalex.org/W3093978547","https://openalex.org/W2953536436","https://openalex.org/W3203790781","https://openalex.org/W4313346231","https://openalex.org/W2738001131","https://openalex.org/W4285785480","https://openalex.org/W2997056298"],"abstract_inverted_index":{"Nowadays":[0],"deep":[1],"learning":[2,97,148],"is":[3,7,39,52,90,99,135,162,174,215,222],"a":[4,165],"tool,":[5],"which":[6,19,89],"used":[8,133,187],"in":[9,22,59,118,146,188],"many":[10,32],"different":[11,56],"pattern":[12],"recognition":[13],"problems.":[14],"For":[15],"achieving":[16],"strong":[17,159],"results,":[18],"are":[20,29,78,151,185],"reported":[21],"literature,":[23],"often":[24,186],"large":[25],"amounts":[26],"of":[27,49,75,102,125,142,177,201,208,219],"data":[28,38,104,127,193,210,221],"necessary.":[30],"In":[31,109,182],"use":[33,218],"cases":[34],"collecting":[35],"or":[36,42],"labeling":[37],"very":[40],"difficult":[41],"not":[43],"possible":[44],"at":[45],"all.":[46],"The":[47,71,171,217],"aim":[48],"this":[50,110],"paper":[51,111],"to":[53,61,66,82,120,190,196],"compare":[54],"three":[55],"algorithmic":[57,87],"approaches":[58],"order":[60,119,189],"deal":[62],"with":[63],"limited":[64],"access":[65],"labeled":[67],"and":[68,73,80,95,161,194,226],"unlabeled":[69,209,220],"data.":[70],"drawbacks":[72],"benefits":[74],"each":[76,83],"method":[77],"shown":[79,158],"compared":[81],"other.":[84],"A":[85],"successful":[86,92],"approach,":[88],"especially":[91],"for":[93,168,211,224],"one-":[94],"few-shot":[96],"problems,":[98],"the":[100,106,123,129,143,175,198,202,206],"usage":[101,124,176,207],"external":[103,126],"during":[105],"classification":[107,203],"task.":[108],"siamese":[112],"neural":[113],"networks":[114,180],"will":[115],"be":[116],"investigated":[117,223],"evaluate":[121],"how":[122],"improves":[128],"accuracy.":[130],"Another":[131],"widely":[132],"approach":[134,173],"consistency":[136,139,169],"regularization.":[137,170],"Using":[138],"regularization":[140],"state":[141],"art":[144],"results":[145,160],"semi-supervised":[147],"(SSL)":[149],"benchmarks":[150],"achieved.":[152],"Virtual":[153],"adversarial":[154,179],"training":[155],"(VAT)":[156],"has":[157],"chosen":[163],"as":[164],"representative":[166],"algorithm":[167],"last":[172],"generative":[178],"(GANs).":[181],"literature":[183],"GANs":[184,225],"create":[191],"additional":[192],"therefor":[195],"increase":[197],"generalization":[199],"capability":[200],"network.":[204],"Furthermore":[205],"further":[212],"performance":[213],"improvement":[214],"considered.":[216],"VAT.":[227]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}