{"id":"https://openalex.org/W6942996664","doi":"https://doi.org/10.15167/maracani-andrea_phd2024-04-12","title":"Knowledge Transferability for Data-Efficient Deep Learning","display_name":"Knowledge Transferability for Data-Efficient Deep Learning","publication_year":2024,"publication_date":"2024-04-12","ids":{"openalex":"https://openalex.org/W6942996664","doi":"https://doi.org/10.15167/maracani-andrea_phd2024-04-12"},"language":"en","primary_location":{"id":"pmh:oai:iris.unige.it:11567/1171035","is_oa":true,"landing_page_url":"https://hdl.handle.net/11567/1171035","pdf_url":"https://unige.iris.cineca.it/bitstream/11567/1171035/3/phdunige_4969220.pdf","source":{"id":"https://openalex.org/S4377196291","display_name":"CINECA IRIS Institutial Research Information System (University of Genoa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I83816512","host_organization_name":"University of Genoa","host_organization_lineage":["https://openalex.org/I83816512"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/doctoralThesis"},"type":"dissertation","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://unige.iris.cineca.it/bitstream/11567/1171035/3/phdunige_4969220.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"MARACANI, ANDREA","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"MARACANI, ANDREA","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10451","display_name":"Mycorrhizal Fungi and Plant Interactions","score":0.5004000067710876,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10451","display_name":"Mycorrhizal Fungi and Plant Interactions","score":0.5004000067710876,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10825","display_name":"Plant Pathogens and Fungal Diseases","score":0.05640000104904175,"subfield":{"id":"https://openalex.org/subfields/1307","display_name":"Cell Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12668","display_name":"Yeasts and Rust Fungi Studies","score":0.04569999873638153,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7605999708175659},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7267000079154968},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5902000069618225},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5855000019073486},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5842000246047974},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.517300009727478},{"id":"https://openalex.org/keywords/transferability","display_name":"Transferability","score":0.5063999891281128},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.49619999527931213},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47859999537467957}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7605999708175659},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7573999762535095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7365000247955322},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7267000079154968},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6079999804496765},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5902000069618225},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5855000019073486},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5842000246047974},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.517300009727478},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.5063999891281128},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.49619999527931213},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47859999537467957},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47530001401901245},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.4131999909877777},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.3828999996185303},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.38260000944137573},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.35839998722076416},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3515999913215637},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3497999906539917},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3070000112056732},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3050000071525574},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2694999873638153},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.25839999318122864}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:iris.unige.it:11567/1171035","is_oa":true,"landing_page_url":"https://hdl.handle.net/11567/1171035","pdf_url":"https://unige.iris.cineca.it/bitstream/11567/1171035/3/phdunige_4969220.pdf","source":{"id":"https://openalex.org/S4377196291","display_name":"CINECA IRIS Institutial Research Information System (University of Genoa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I83816512","host_organization_name":"University of Genoa","host_organization_lineage":["https://openalex.org/I83816512"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/doctoralThesis"},{"id":"doi:10.15167/maracani-andrea_phd2024-04-12","is_oa":true,"landing_page_url":"https://doi.org/10.15167/maracani-andrea_phd2024-04-12","pdf_url":null,"source":{"id":"https://openalex.org/S7407050993","display_name":"Universit\u00e0 degli Studi di Genova","issn_l":null,"issn":null,"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":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Other"}],"best_oa_location":{"id":"pmh:oai:iris.unige.it:11567/1171035","is_oa":true,"landing_page_url":"https://hdl.handle.net/11567/1171035","pdf_url":"https://unige.iris.cineca.it/bitstream/11567/1171035/3/phdunige_4969220.pdf","source":{"id":"https://openalex.org/S4377196291","display_name":"CINECA IRIS Institutial Research Information System (University of Genoa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I83816512","host_organization_name":"University of Genoa","host_organization_lineage":["https://openalex.org/I83816512"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/doctoralThesis"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5492220520973206,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W6942996664.pdf","grobid_xml":"https://content.openalex.org/works/W6942996664.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0,79,131,308],"Learning":[1,60],"has":[2],"demonstrated":[3],"remarkable":[4],"progress":[5],"in":[6,54,67,114,129,155,208,240,295,339,359],"various":[7],"Computer":[8],"Vision":[9],"tasks.":[10],"However,":[11],"its":[12,88,223],"effectiveness":[13],"often":[14,29],"relies":[15],"on":[16,83,90,146,165,247],"the":[17,44,74,147,185,289,303,321],"availability":[18,31],"of":[19,32,104,140,149,175,255,262,306],"large,":[20],"well-annotated":[21],"datasets.":[22],"In":[23,310],"many":[24,274],"practical":[25],"scenarios,":[26],"there":[27],"is":[28,95,107,258],"limited":[30],"such":[33,312],"data.":[34],"Furthermore,":[35,194,368],"collecting":[36],"or":[37,51,97,386],"labeling":[38],"more":[39,282,348],"samples":[40],"that":[41,325],"align":[42],"with":[43,229,270,388],"post-deployment":[45],"environment":[46],"can":[47,328],"sometimes":[48],"be":[49],"challenging":[50],"impossible,":[52],"resulting":[53],"reduced":[55],"and":[56,110,126,178,203,267,281,292,319,342,347,365],"sub-optimal":[57],"performance.":[58],"Transfer":[59,263],"(TL)":[61],"emerges":[62],"as":[63,313,372],"a":[64,78,137,172,191,213,241,259,286,330,373],"promising":[65],"solution":[66],"these":[68],"contexts,":[69],"offering":[70,356],"methods":[71],"to":[72,86,108,181,235,273],"leverage":[73],"knowledge":[75],"acquired":[76],"by":[77,222],"Neural":[80],"Network":[81],"(DNN)":[82],"one":[84],"task":[85],"enhance":[87],"performance":[89],"another,":[91],"especially":[92],"when":[93],"data":[94,266,334],"scarce,":[96],"labels":[98],"are":[99,184],"absent.":[100],"The":[101],"main":[102],"objective":[103],"this":[105,256,296],"project":[106],"study":[109,164,298],"analyze":[111],"TL":[112,142,323],"methodologies":[113,239,353],"depth,":[115],"providing":[116],"novel":[117],"perspectives,":[118],"suggesting":[119],"new":[120,197,214,271],"directions":[121],"both":[122,277],"for":[123,190,218,244,302,337,376,380],"real-world":[124,156,279],"applications":[125,280,311],"future":[127],"research":[128,297],"data-efficient":[130,307],"Learning.
\\nTo":[132],"achieve":[133],"this,":[134],"we":[135,195,326],"present":[136],"comprehensive":[138,260],"analysis":[139],"prevalent":[141],"pipelines,":[143],"particularly":[144],"focusing":[145,246],"fine-tuning":[148],"DNNs":[150],"weights":[151],"from":[152],"pre-trained":[153],"models":[154,362],"scenarios.":[157],"We":[158,210],"also":[159,211],"conduct":[160],"an":[161],"extensive":[162],"experimental":[163],"Domain":[166,215,237],"Adaptation":[167,216,238],"techniques,":[168],"assessing":[169],"numerous":[170],"datasets,":[171],"wide":[173],"range":[174],"DNN":[176],"architectures":[177],"pre-training":[179],"strategies":[180],"determine":[182],"which":[183,226],"most":[186],"important":[187],"design":[188],"choices":[189],"successful":[192],"transferability.":[193],"develop":[196],"algorithms":[198],"aimed":[199],"at":[200],"enhancing":[201],"data-efficiency":[202],"adaptability":[204],"(like":[205],"Object":[206],"Detection":[207],"robotics).":[209],"introduce":[212,327],"technique":[217],"Image":[219],"Classification,":[220],"characterized":[221],"straightforward":[224],"design,":[225],"favorably":[227],"competes":[228],"state-of-the-art":[230],"approaches.":[231],"Our":[232,352],"exploration":[233,381],"extends":[234],"validate":[236],"Sim-to-Real":[242],"application":[243],"robotics,":[245,314],"surface":[248],"recognition":[249],"using":[250],"vision-based":[251],"tactile":[252],"sensors.
\\nThe":[253],"result":[254],"work":[257],"overview":[261],"Learning,":[264],"emphasizing":[265],"label":[268],"efficiency,":[269],"solutions":[272],"challenges,":[275],"addressing":[276],"specific":[278],"general":[283],"algorithmic":[284],"paradigms.
\\nFrom":[285],"broader":[287],"perspective,":[288],"algorithms,":[290],"analyses,":[291],"discoveries":[293],"presented":[294],"have":[299],"substantial":[300],"implications":[301],"expansive":[304],"field":[305],"Learning.":[309],"autonomous":[315],"vehicles,":[316],"industrial":[317],"automation":[318],"healthcare,":[320],"refined":[322],"techniques":[324],"play":[329],"crucial":[331],"role.":[332],"Enhancing":[333],"efficiency":[335],"allows":[336],"reductions":[338],"computational":[340],"costs":[341],"training":[343],"times,":[344],"facilitating":[345],"faster":[346],"precise":[349],"model":[350],"deployments.":[351],"emphasize":[354],"adaptability,":[355],"great":[357],"value":[358],"situations":[360],"where":[361],"face":[363],"varied":[364],"dynamic":[366],"environments.":[367],"our":[369],"findings":[370],"serve":[371],"robust":[374],"foundation":[375],"subsequent":[377],"research,":[378],"allowing":[379],"into":[382],"deeper":[383],"domain-specific":[384],"adaptations":[385],"integration":[387],"emerging":[389],"AI":[390],"methodologies.":[391]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}