{"id":"https://openalex.org/W7126026254","doi":"https://doi.org/10.1007/s10462-026-11491-z","title":"Deep transfer learning for image classification: a survey","display_name":"Deep transfer learning for image classification: a survey","publication_year":2026,"publication_date":"2026-01-29","ids":{"openalex":"https://openalex.org/W7126026254","doi":"https://doi.org/10.1007/s10462-026-11491-z"},"language":"en","primary_location":{"id":"doi:10.1007/s10462-026-11491-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10462-026-11491-z","pdf_url":null,"source":{"id":"https://openalex.org/S122814990","display_name":"Artificial Intelligence Review","issn_l":"0269-2821","issn":["0269-2821","1573-7462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Review","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/s10462-026-11491-z","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124089805","display_name":"Jo Plested","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jo Plested","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124295884","display_name":"Musa Phiri","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Musa Phiri","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5124257415","display_name":"Tom Gedeon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tom Gedeon","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5124089805"],"corresponding_institution_ids":[],"apc_list":{"value":2490,"currency":"EUR","value_usd":3090},"apc_paid":{"value":2490,"currency":"EUR","value_usd":3090},"fwci":69.51,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.99789651,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"59","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.13369999825954437,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.13369999825954437,"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/T11448","display_name":"Face recognition and analysis","score":0.05829999968409538,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.04780000075697899,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.8349000215530396},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7682999968528748},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6858000159263611},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6000999808311462},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5163999795913696},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49559998512268066},{"id":"https://openalex.org/keywords/knowledge-transfer","display_name":"Knowledge transfer","score":0.4814999997615814}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.8349000215530396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7858999967575073},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7682999968528748},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6948999762535095},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6858000159263611},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6000999808311462},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5256999731063843},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5163999795913696},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49559998512268066},{"id":"https://openalex.org/C2776960227","wikidata":"https://www.wikidata.org/wiki/Q2586354","display_name":"Knowledge transfer","level":2,"score":0.4814999997615814},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4406999945640564},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.373199999332428},{"id":"https://openalex.org/C77075516","wikidata":"https://www.wikidata.org/wiki/Q6027324","display_name":"Inductive transfer","level":5,"score":0.3149000108242035},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3089999854564667},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2671999931335449},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2587999999523163}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10462-026-11491-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10462-026-11491-z","pdf_url":null,"source":{"id":"https://openalex.org/S122814990","display_name":"Artificial Intelligence Review","issn_l":"0269-2821","issn":["0269-2821","1573-7462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Review","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10462-026-11491-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10462-026-11491-z","pdf_url":null,"source":{"id":"https://openalex.org/S122814990","display_name":"Artificial Intelligence Review","issn_l":"0269-2821","issn":["0269-2821","1573-7462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Review","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320965","display_name":"University of New South Wales","ror":"https://ror.org/03r8z3t63"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":114,"referenced_works":["https://openalex.org/W12634471","https://openalex.org/W343636949","https://openalex.org/W1722318740","https://openalex.org/W1821938769","https://openalex.org/W1861492603","https://openalex.org/W1977295328","https://openalex.org/W1993309459","https://openalex.org/W2017814585","https://openalex.org/W2047643928","https://openalex.org/W2067713319","https://openalex.org/W2081580037","https://openalex.org/W2097117768","https://openalex.org/W2104094955","https://openalex.org/W2108598243","https://openalex.org/W2138011018","https://openalex.org/W2149466042","https://openalex.org/W2152161678","https://openalex.org/W2154740476","https://openalex.org/W2155904486","https://openalex.org/W2164943005","https://openalex.org/W2165698076","https://openalex.org/W2194321275","https://openalex.org/W2194775991","https://openalex.org/W2253728219","https://openalex.org/W2282821441","https://openalex.org/W2296043783","https://openalex.org/W2321533354","https://openalex.org/W2395579298","https://openalex.org/W2519648241","https://openalex.org/W2533598788","https://openalex.org/W2591924527","https://openalex.org/W2593768305","https://openalex.org/W2606209624","https://openalex.org/W2732026016","https://openalex.org/W2786808285","https://openalex.org/W2797977484","https://openalex.org/W2798381792","https://openalex.org/W2804905867","https://openalex.org/W2804935296","https://openalex.org/W2887280559","https://openalex.org/W2906598409","https://openalex.org/W2911801153","https://openalex.org/W2962843773","https://openalex.org/W2963420272","https://openalex.org/W2963460174","https://openalex.org/W2963470893","https://openalex.org/W2963703197","https://openalex.org/W2963709863","https://openalex.org/W2963870446","https://openalex.org/W2964309882","https://openalex.org/W2968584961","https://openalex.org/W2969656782","https://openalex.org/W2970677506","https://openalex.org/W2972093541","https://openalex.org/W2979549710","https://openalex.org/W2980113592","https://openalex.org/W2981848390","https://openalex.org/W2983943451","https://openalex.org/W2991391304","https://openalex.org/W2993751684","https://openalex.org/W2995472160","https://openalex.org/W3002093512","https://openalex.org/W3003448987","https://openalex.org/W3012255272","https://openalex.org/W3021632667","https://openalex.org/W3023371261","https://openalex.org/W3030489213","https://openalex.org/W3034942609","https://openalex.org/W3035160371","https://openalex.org/W3037032032","https://openalex.org/W3041133507","https://openalex.org/W3042425239","https://openalex.org/W3097217077","https://openalex.org/W3101525400","https://openalex.org/W3108004548","https://openalex.org/W3120129399","https://openalex.org/W3120430728","https://openalex.org/W3127294368","https://openalex.org/W3132898468","https://openalex.org/W3135562100","https://openalex.org/W3136987292","https://openalex.org/W3172854222","https://openalex.org/W3174189432","https://openalex.org/W3177096435","https://openalex.org/W3179442871","https://openalex.org/W3209452342","https://openalex.org/W3209987414","https://openalex.org/W3216083537","https://openalex.org/W4200453770","https://openalex.org/W4206573688","https://openalex.org/W4206657577","https://openalex.org/W4221142320","https://openalex.org/W4255421341","https://openalex.org/W4287660544","https://openalex.org/W4288083516","https://openalex.org/W4307844773","https://openalex.org/W4312651322","https://openalex.org/W4313156423","https://openalex.org/W4324142429","https://openalex.org/W4367598041","https://openalex.org/W4385346231","https://openalex.org/W4386065512","https://openalex.org/W4386242137","https://openalex.org/W4387602998","https://openalex.org/W4390872006","https://openalex.org/W4391457558","https://openalex.org/W4391547566","https://openalex.org/W4396542861","https://openalex.org/W4399728346","https://openalex.org/W4402545715","https://openalex.org/W4406611091","https://openalex.org/W4408673719","https://openalex.org/W4413144850","https://openalex.org/W4415795252"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Deep":[1],"neural":[2,7],"networks":[3,8],"such":[4],"as":[5,91],"convolutional":[6],"(CNNs)":[9],"and":[10,114,119,130,150,167,189,232,274,277,292,298,307],"transformers":[11],"have":[12,81],"achieved":[13],"many":[14,48,247,282],"successes":[15],"in":[16,19,106,137,163,178],"image":[17,31,95,140,195],"classification":[18,32,96],"recent":[20,153],"years.":[21],"It":[22],"has":[23,155,210,216,254],"been":[24,82,156,211,255],"consistently":[25],"demonstrated":[26],"that":[27,85,109,242,290,317],"best":[28,64],"practice":[29],"for":[30,55,103,170,194,296,305],"is":[33,101,112,289],"when":[34,268],"large":[35,56,297],"deep":[36,88,127],"models":[37],"can":[38,74],"be":[39,67,236,258,266],"trained":[40],"on":[41],"abundant":[42],"labeled":[43],"data.":[44],"However,":[45],"there":[46,80],"are":[47,166,264,303],"real":[49],"world":[50],"scenarios":[51],"where":[52,152,160,207,214,228,251],"the":[53,63,107,115,131,144,148,161,174,187,229,249,272,278,286],"requirement":[54],"amounts":[57],"of":[58,147,186,191,206,248,283],"training":[59],"data":[60],"to":[61,94,135,139,172,176,202,218,226,257,265,320],"get":[62],"performance":[65,263],"cannot":[66],"met.":[68],"In":[69,121,281],"these":[70,179,284],"scenarios,":[71],"transfer":[72,89,128,192,208,252],"learning":[73,90,129,193,209,253],"help":[75],"improve":[76],"performance.":[77],"To":[78],"date,":[79],"no":[83],"surveys":[84],"comprehensively":[86],"review":[87],"it":[92,100,133,200,215,234],"relates":[93],"overall.":[97],"We":[98,142,158,182,240,313],"believe":[99],"important":[102],"future":[104],"progress":[105,154,173],"field":[108,149,175],"current":[110,145,164],"knowledge":[111,165,180],"collated":[113],"overarching":[116,204],"patterns":[117,205],"analyzed":[118],"discussed.":[120],"this":[122,244],"survey":[123,143],"we":[124],"formally":[125],"define":[126],"problem":[132,288],"attempts":[134],"solve":[136],"relation":[138],"classification.":[141,196],"state":[146],"identify":[151,314],"made.":[157],"show":[159],"gaps":[162],"make":[168,199],"suggestions":[169],"how":[171,233],"fill":[177],"gaps.":[181],"present":[183],"new":[184,245],"taxonomies":[185,198],"solution":[188],"applications":[190,250],"These":[197],"easier":[201],"see":[203],"effective":[212],"and,":[213],"failed":[217],"fulfil":[219],"its":[220],"potential.":[221],"This":[222],"also":[223],"allows":[224],"us":[225],"suggest":[227],"problems":[230],"lie":[231],"could":[235,318],"used":[237,304],"more":[238],"effectively.":[239],"demonstrate":[241],"under":[243],"taxonomy,":[246],"shown":[256],"ineffective":[259],"or":[260],"even":[261],"hinder":[262],"expected":[267],"taking":[269],"into":[270],"account":[271],"source":[273],"target":[275,301,311],"datasets":[276,302],"techniques":[279],"used.":[280],"cases,":[285],"key":[287],"methods":[291],"hyperparameter":[293],"settings":[294],"designed":[295],"very":[299],"similar":[300,310],"smaller":[306],"much":[308],"less":[309],"datasets.":[312],"alternative":[315],"choices":[316],"lead":[319],"better":[321],"outcomes.":[322]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2026-01-30T00:00:00"}