{"id":"https://openalex.org/W4312060039","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892393","title":"Effect of pre-training scale on intra- and inter-domain, full and few-shot transfer learning for natural and X-Ray chest images","display_name":"Effect of pre-training scale on intra- and inter-domain, full and few-shot transfer learning for natural and X-Ray chest images","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312060039","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892393"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892393","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":"2161-4407","issn":["2161-4407"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5050394079","display_name":"Mehdi Cherti","orcid":"https://orcid.org/0000-0001-5865-0469"},"institutions":[{"id":"https://openalex.org/I171892758","display_name":"Forschungszentrum J\u00fclich","ror":"https://ror.org/02nv7yv05","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I171892758"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mehdi Cherti","raw_affiliation_strings":["Juelich Supercomputing Center, Helmholtz AI, Research Center,Juelich,Germany","Juelich Supercomputing Center, Helmholtz AI, Research Center, Juelich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Juelich Supercomputing Center, Helmholtz AI, Research Center,Juelich,Germany","institution_ids":["https://openalex.org/I171892758"]},{"raw_affiliation_string":"Juelich Supercomputing Center, Helmholtz AI, Research Center, Juelich, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085870953","display_name":"Jenia Jitsev","orcid":"https://orcid.org/0000-0002-1221-7851"},"institutions":[{"id":"https://openalex.org/I171892758","display_name":"Forschungszentrum J\u00fclich","ror":"https://ror.org/02nv7yv05","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I171892758"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jenia Jitsev","raw_affiliation_strings":["Juelich Supercomputing Center, Helmholtz AI, Research Center,Juelich,Germany","Juelich Supercomputing Center, Helmholtz AI, Research Center, Juelich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Juelich Supercomputing Center, Helmholtz AI, Research Center,Juelich,Germany","institution_ids":["https://openalex.org/I171892758"]},{"raw_affiliation_string":"Juelich Supercomputing Center, Helmholtz AI, Research Center, Juelich, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I171892758"],"apc_list":null,"apc_paid":null,"fwci":9.2935,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.98815126,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11894","display_name":"Radiology practices and education","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.7776134014129639},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5940396189689636},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5492796301841736},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5216089487075806},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5117959380149841},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4846278131008148},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.47208353877067566},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.4255324900150299},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3609328269958496},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.22428980469703674},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.17830190062522888},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14379224181175232},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10619816184043884},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.08045962452888489},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.06711158156394958}],"concepts":[{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.7776134014129639},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5940396189689636},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5492796301841736},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5216089487075806},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5117959380149841},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4846278131008148},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.47208353877067566},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.4255324900150299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3609328269958496},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.22428980469703674},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.17830190062522888},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14379224181175232},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10619816184043884},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.08045962452888489},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.06711158156394958},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","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/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/ijcnn55064.2022.9892393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892393","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":"2161-4407","issn":["2161-4407"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 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":57,"referenced_works":["https://openalex.org/W1904878066","https://openalex.org/W1977295328","https://openalex.org/W2062118960","https://openalex.org/W2108598243","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2203224402","https://openalex.org/W2533598788","https://openalex.org/W2611650229","https://openalex.org/W2912664121","https://openalex.org/W2947706148","https://openalex.org/W2962843773","https://openalex.org/W2963466845","https://openalex.org/W2963518130","https://openalex.org/W2995225687","https://openalex.org/W3001279689","https://openalex.org/W3005030567","https://openalex.org/W3008526508","https://openalex.org/W3035003500","https://openalex.org/W3035160371","https://openalex.org/W3097217077","https://openalex.org/W3100859887","https://openalex.org/W3101156210","https://openalex.org/W3105081694","https://openalex.org/W3118608800","https://openalex.org/W3120430728","https://openalex.org/W3128633047","https://openalex.org/W3134642945","https://openalex.org/W3166396011","https://openalex.org/W3172942063","https://openalex.org/W3216631677","https://openalex.org/W4200030970","https://openalex.org/W4206410067","https://openalex.org/W4286889064","https://openalex.org/W4287203292","https://openalex.org/W4287390226","https://openalex.org/W4288076043","https://openalex.org/W4289300273","https://openalex.org/W4292779060","https://openalex.org/W4301239768","https://openalex.org/W6639867372","https://openalex.org/W6748645090","https://openalex.org/W6756592394","https://openalex.org/W6763301180","https://openalex.org/W6772383348","https://openalex.org/W6773574953","https://openalex.org/W6774908330","https://openalex.org/W6778883912","https://openalex.org/W6779101013","https://openalex.org/W6779977557","https://openalex.org/W6790209031","https://openalex.org/W6790391859","https://openalex.org/W6790428460","https://openalex.org/W6791353385","https://openalex.org/W6791376898","https://openalex.org/W6794559225","https://openalex.org/W6797602710"],"related_works":["https://openalex.org/W2497720472","https://openalex.org/W4292659306","https://openalex.org/W3044321615","https://openalex.org/W2806221744","https://openalex.org/W2326937258","https://openalex.org/W394267150","https://openalex.org/W2773965352","https://openalex.org/W4294892107","https://openalex.org/W2357748469","https://openalex.org/W2392917037"],"abstract_inverted_index":{"Increasing":[0],"model,":[1],"data":[2,55,123,219,240,263],"and":[3,18,30,53,69,75,121,125,138,161,188,233],"compute":[4],"budget":[5],"scale":[6,43,65,96,124,157,175,241],"in":[7,21,27,46,57,108,180,242,267],"the":[8,38,82,192,243,268],"pre-training":[9,107,156,174,244],"has":[10],"been":[11],"shown":[12],"to":[13,93,102,142,154,172,223,251],"strongly":[14],"improve":[15],"model":[16,232],"generalization":[17],"transfer":[19,139,222,250],"learning":[20],"vast":[22],"line":[23],"of":[24,41,48,63],"work":[25],"done":[26,45],"language":[28],"modeling":[29],"natural":[31,109,130,144,204,237],"image":[32,110,238],"recognition.":[33],"However,":[34],"most":[35],"studies":[36],"on":[37,176,201,214,258],"positive":[39],"effect":[40,62],"larger":[42,64,155,173,177],"were":[44],"scope":[47],"in-domain":[49,68],"setting,":[50],"with":[51],"source":[52,122,239,262],"target":[54],"being":[56,127],"close":[58],"proximity.":[59],"To":[60],"study":[61],"for":[66,81,97,106,158,185,189],"both":[67],"out-of-domain":[70,249],"setting":[71],"when":[72,220],"performing":[73,221],"full":[74,181],"few-shot":[76,190],"transfer,":[77,167],"we":[78,168],"combine":[79],"here":[80],"first":[83],"time":[84],"large,":[85],"openly":[86],"available":[87,216,266],"medical":[88,98,134,146,217,235,252,260],"X-Ray":[89,136,178,218,225],"chest":[90,135],"imaging":[91,99],"datasets":[92],"reach":[94],"a":[95],"domain":[100,253],"comparable":[101],"ImageNet-1k,":[103],"routinely":[104],"used":[105],"domain.":[111],"We":[112,149,227],"then":[113],"conduct":[114],"supervised":[115],"pre-training,":[116],"while":[117,184],"varying":[118],"network":[119],"size":[120],"domain,":[126],"either":[128],"large":[129,133,198,203,224,259],"(ImageNet-1k/21k)":[131],"or":[132,145,209],"datasets,":[137],"pre-trained":[140,200,213],"models":[141],"different":[143],"targets11Repository:":[147],"https://github.com/SLAMPAI/large-scale-pretraining-transfer,":[148],"observe":[150],"strong":[151],"improvement":[152,193],"due":[153,171],"intra-domain":[159],"natural-natural":[160],"medical-medical":[162],"transfer.":[163],"For":[164],"inter-domain":[165],"natural-medical":[166],"find":[169],"improvements":[170],"targets":[179,187],"shot":[182],"regime,":[183],"smaller":[186],"regime":[191],"is":[194],"not":[195,265],"visible.":[196],"Remarkably,":[197],"networks":[199,212],"very":[202],"ImageNet-21k":[205],"are":[206],"as":[207],"good":[208],"better":[210],"than":[211],"largest":[215],"targets.":[226],"conclude":[228],"that":[229],"substantially":[230],"increasing":[231],"generic,":[234],"domain-agnostic":[236],"can":[245],"enable":[246],"high":[247],"quality":[248],"specific":[254],"targets,":[255],"removing":[256],"dependency":[257],"domain-specific":[261],"often":[264],"practice.":[269]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2023-01-04T00:00:00"}