{"id":"https://openalex.org/W4410639559","doi":"https://doi.org/10.1109/tnnls.2025.3569797","title":"Boosting Memory Efficiency in Transfer Learning for High-Resolution Medical Image Classification","display_name":"Boosting Memory Efficiency in Transfer Learning for High-Resolution Medical Image Classification","publication_year":2025,"publication_date":"2025-05-23","ids":{"openalex":"https://openalex.org/W4410639559","doi":"https://doi.org/10.1109/tnnls.2025.3569797","pmid":"https://pubmed.ncbi.nlm.nih.gov/40408202"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3569797","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3569797","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5079055375","display_name":"Yijin Huang","orcid":"https://orcid.org/0000-0002-0988-0134"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yijin Huang","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025516568","display_name":"Pujin Cheng","orcid":"https://orcid.org/0009-0000-4844-5146"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pujin Cheng","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084754494","display_name":"Roger Tam","orcid":"https://orcid.org/0000-0002-4593-2587"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Roger Tam","raw_affiliation_strings":["School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080168999","display_name":"Xiaoying Tang","orcid":"https://orcid.org/0000-0002-7549-6560"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoying Tang","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079055375"],"corresponding_institution_ids":["https://openalex.org/I3045169105"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17588303,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"9","first_page":"17280","last_page":"17294"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9104999899864197,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9104999899864197,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.8549655675888062},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.564717710018158},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.551081657409668},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5324146747589111},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38448211550712585},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33670538663864136},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3276231586933136}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8549655675888062},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.564717710018158},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.551081657409668},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5324146747589111},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38448211550712585},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33670538663864136},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3276231586933136}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":true},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":true},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008568","descriptor_name":"Memory","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D008568","descriptor_name":"Memory","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3569797","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3569797","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:40408202","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40408202","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3419736287","display_name":null,"funder_award_id":"T2422012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5564020545","display_name":null,"funder_award_id":"2023YFC2415400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7508651374","display_name":null,"funder_award_id":"62071210","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1904878066","https://openalex.org/W1969496006","https://openalex.org/W2108598243","https://openalex.org/W2395579298","https://openalex.org/W2776937175","https://openalex.org/W2932083555","https://openalex.org/W2948685905","https://openalex.org/W3115894062","https://openalex.org/W3151130473","https://openalex.org/W3159481202","https://openalex.org/W3176828726","https://openalex.org/W3198377975","https://openalex.org/W4205991051","https://openalex.org/W4306369316","https://openalex.org/W4312310776","https://openalex.org/W4312651322","https://openalex.org/W4313125078","https://openalex.org/W4322766882","https://openalex.org/W4378516647","https://openalex.org/W4379229760","https://openalex.org/W4382465573","https://openalex.org/W4385245566","https://openalex.org/W4386065718","https://openalex.org/W4386697749","https://openalex.org/W4387665871","https://openalex.org/W4389196682","https://openalex.org/W4390872786","https://openalex.org/W4390874575","https://openalex.org/W4391109864","https://openalex.org/W4391582571","https://openalex.org/W4400229603","https://openalex.org/W4400321119","https://openalex.org/W4401852105","https://openalex.org/W4403069792","https://openalex.org/W4403619652","https://openalex.org/W4408634392"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W1549363203","https://openalex.org/W2147697413","https://openalex.org/W2154063878","https://openalex.org/W4231274751","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W3082059448","https://openalex.org/W4313640622"],"abstract_inverted_index":{"The":[0,149],"success":[1],"of":[2,26,140,206,224,230],"large-scale":[3],"pretrained":[4,28,45,121,126,179],"models":[5,46],"has":[6,36],"established":[7],"fine-tuning":[8,21,235],"as":[9,39,64,72,74],"a":[10,27,40,88,115,124,144],"standard":[11],"method":[12,90],"for":[13,43,62,92,234],"achieving":[14],"significant":[15],"improvements":[16],"in":[17],"downstream":[18,48],"tasks.":[19,49],"However,":[20],"the":[22,53,65,75,100,138,160,174,194,225,231],"entire":[23,237],"parameter":[24,76],"set":[25],"model":[29,55,127],"is":[30,69,242],"costly.":[31],"Parameter-efficient":[32],"transfer":[33,111],"learning":[34,112],"(PETL)":[35],"recently":[37],"emerged":[38],"cost-effective":[41],"alternative":[42],"adapting":[44],"to":[47,105,155,168,177,190],"Despite":[50],"its":[51],"advantages,":[52],"increasing":[54],"size":[56],"and":[57,119,132,142,185,210,228],"input":[58],"resolution":[59],"present":[60],"challenges":[61],"PETL,":[63],"training":[66,101,114],"memory":[67,102,170,232],"consumption":[68,103],"not":[70],"reduced":[71],"effectively":[73],"usage.":[77,171],"In":[78],"this":[79],"article,":[80],"we":[81,136,181],"introduce":[82],"fine-grained":[83,130,157,183],"prompt":[84],"tuning":[85],"plus":[86],"(FPT+),":[87],"PETL":[89,107,219],"designed":[91],"high-resolution":[93,153],"medical":[94,203],"image":[95,204],"classification,":[96],"which":[97,188],"significantly":[98],"reduces":[99],"compared":[104],"other":[106,218],"methods.":[108],"FPT+":[109,200,216],"performs":[110],"by":[113],"lightweight":[116,146],"side":[117,147,161,175],"network":[118,162,176],"accessing":[120],"knowledge":[122],"from":[123],"large":[125],"(LPM)":[128],"through":[129,193],"prompts":[131,184],"fusion":[133,186],"modules.":[134],"Specifically,":[135],"freeze":[137],"LPM":[139,151],"interest":[141],"construct":[143],"learnable":[145,226],"network.":[148],"frozen":[150],"processes":[152],"images":[154,167],"extract":[156],"features,":[158],"while":[159],"employs":[163],"corresponding":[164],"downsampled":[165],"low-resolution":[166],"minimize":[169],"To":[172],"enable":[173],"leverage":[178],"knowledge,":[180],"propose":[182],"modules,":[187],"collaborate":[189],"summarize":[191],"information":[192],"LPM's":[195],"intermediate":[196],"activations.":[197],"We":[198],"evaluate":[199],"on":[201],"eight":[202],"datasets":[205],"varying":[207],"sizes,":[208],"modalities,":[209],"complexities.":[211],"Experimental":[212],"results":[213],"demonstrate":[214],"that":[215],"outperforms":[217],"methods,":[220],"using":[221],"only":[222],"1.03%":[223],"parameters":[227],"3.18%":[229],"required":[233],"an":[236],"ViT-B":[238],"model.":[239],"Our":[240],"code":[241],"available":[243],"https://github.com/YijinHuang/FPT.":[244]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}