{"id":"https://openalex.org/W7124736675","doi":"https://doi.org/10.48550/arxiv.2601.11235","title":"Bio-inspired fine-tuning for selective transfer learning in image classification","display_name":"Bio-inspired fine-tuning for selective transfer learning in image classification","publication_year":2026,"publication_date":"2026-01-16","ids":{"openalex":"https://openalex.org/W7124736675","doi":"https://doi.org/10.48550/arxiv.2601.11235"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.11235","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.11235","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.11235","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123328043","display_name":"Ana Davila","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Davila, Ana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081397540","display_name":"Jacinto Colan","orcid":"https://orcid.org/0000-0002-8833-2215"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Colan, Jacinto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067104092","display_name":"Yasuhisa Hasegawa","orcid":"https://orcid.org/0000-0001-9917-098X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hasegawa, Yasuhisa","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":false,"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":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.7552000284194946,"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":0.7552000284194946,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.07400000095367432,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.04179999977350235,"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/transfer-of-learning","display_name":"Transfer of learning","score":0.743399977684021},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5724999904632568},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5378999710083008},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.48980000615119934},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4652000069618225},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4578000009059906},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.44749999046325684},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.421999990940094}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7445999979972839},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.743399977684021},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.667900025844574},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5724999904632568},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5378999710083008},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5230000019073486},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.48980000615119934},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4652000069618225},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4578000009059906},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.44749999046325684},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.421999990940094},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41499999165534973},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.3111000061035156},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C2983685735","wikidata":"https://www.wikidata.org/wiki/Q5227355","display_name":"Data source","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.11235","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.11235","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.11235","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.11235","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning":[1,20,62,72],"has":[2],"significantly":[3],"advanced":[4],"image":[5,82],"analysis":[6],"across":[7,124],"diverse":[8],"domains":[9,42,89],"but":[10],"often":[11],"depends":[12],"on":[13,80,144],"large,":[14],"annotated":[15],"datasets":[16],"for":[17,74],"success.":[18],"Transfer":[19],"addresses":[21],"this":[22],"challenge":[23],"by":[24,63],"utilizing":[25,56],"pre-trained":[26],"models":[27],"to":[28,68,111],"tackle":[29],"new":[30],"tasks":[31],"with":[32],"limited":[33],"labeled":[34],"data.":[35],"However,":[36],"discrepancies":[37],"between":[38],"source":[39,148],"and":[40,70,87,98,106,115],"target":[41],"can":[43],"hinder":[44],"effective":[45],"transfer":[46,61],"learning.":[47],"We":[48],"introduce":[49],"BioTune,":[50],"a":[51],"novel":[52],"adaptive":[53],"fine-tuning":[54,102],"technique":[55],"evolutionary":[57],"optimization.":[58],"BioTune":[59,94,119],"enhances":[60],"optimally":[64],"choosing":[65],"which":[66],"layers":[67],"freeze":[69],"adjusting":[71],"rates":[73],"unfrozen":[75],"layers.":[76],"Through":[77],"extensive":[78],"evaluation":[79],"nine":[81],"classification":[83],"datasets,":[84],"spanning":[85],"natural":[86],"specialized":[88],"such":[90],"as":[91],"medical":[92],"imaging,":[93],"demonstrates":[95],"superior":[96],"accuracy":[97],"efficiency":[99],"over":[100],"state-of-the-art":[101],"methods,":[103],"including":[104],"AutoRGN":[105],"LoRA,":[107],"highlighting":[108],"its":[109,130],"adaptability":[110],"various":[112],"data":[113],"characteristics":[114],"distribution":[116],"changes.":[117],"Additionally,":[118],"consistently":[120],"achieves":[121],"top":[122],"performance":[123],"four":[125],"different":[126],"CNN":[127],"architectures,":[128],"underscoring":[129],"flexibility.":[131],"Ablation":[132],"studies":[133],"provide":[134],"valuable":[135],"insights":[136],"into":[137],"the":[138],"impact":[139],"of":[140],"BioTune's":[141],"key":[142],"components":[143],"overall":[145],"performance.":[146],"The":[147],"code":[149],"is":[150],"available":[151],"at":[152],"https://github.com/davilac/BioTune.":[153]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-01-20T00:00:00"}