{"id":"https://openalex.org/W7125960603","doi":"https://doi.org/10.1109/smc58881.2025.11342704","title":"CF-ViT: Cross-Feature Vision Transformer for Improving Feature Learning on Tiny Datasets","display_name":"CF-ViT: Cross-Feature Vision Transformer for Improving Feature Learning on Tiny Datasets","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125960603","doi":"https://doi.org/10.1109/smc58881.2025.11342704"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11342704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5124082135","display_name":"Chunlei Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116723","display_name":"Robotics Research (United States)","ror":"https://ror.org/020w2fr77","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116723"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chunlei Meng","raw_affiliation_strings":["Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433","institution_ids":["https://openalex.org/I4210116723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124099887","display_name":"Wei Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116723","display_name":"Robotics Research (United States)","ror":"https://ror.org/020w2fr77","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116723"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Lin","raw_affiliation_strings":["Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433","institution_ids":["https://openalex.org/I4210116723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124134152","display_name":"Jiacheng Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiacheng Yang","raw_affiliation_strings":["Jihua Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jihua Laboratory","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124054466","display_name":"Yi Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116723","display_name":"Robotics Research (United States)","ror":"https://ror.org/020w2fr77","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116723"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi Liu","raw_affiliation_strings":["Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433","institution_ids":["https://openalex.org/I4210116723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124118409","display_name":"Hongda Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116723","display_name":"Robotics Research (United States)","ror":"https://ror.org/020w2fr77","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116723"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongda Zhang","raw_affiliation_strings":["Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433","institution_ids":["https://openalex.org/I4210116723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124067152","display_name":"Yuning Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116723","display_name":"Robotics Research (United States)","ror":"https://ror.org/020w2fr77","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116723"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuning Chen","raw_affiliation_strings":["Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433","institution_ids":["https://openalex.org/I4210116723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124095175","display_name":"Bowen Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116723","display_name":"Robotics Research (United States)","ror":"https://ror.org/020w2fr77","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116723"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bowen Liu","raw_affiliation_strings":["Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433","institution_ids":["https://openalex.org/I4210116723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124142667","display_name":"Ziqin Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116723","display_name":"Robotics Research (United States)","ror":"https://ror.org/020w2fr77","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116723"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziqin Zhou","raw_affiliation_strings":["Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433","institution_ids":["https://openalex.org/I4210116723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124058344","display_name":"Chun Ouyang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116723","display_name":"Robotics Research (United States)","ror":"https://ror.org/020w2fr77","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116723"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chun Ouyang","raw_affiliation_strings":["Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433","institution_ids":["https://openalex.org/I4210116723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067539236","display_name":"Zhongxue Gan","orcid":"https://orcid.org/0000-0003-3873-5187"},"institutions":[{"id":"https://openalex.org/I4210116723","display_name":"Robotics Research (United States)","ror":"https://ror.org/020w2fr77","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116723"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhongxue Gan","raw_affiliation_strings":["Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433","institution_ids":["https://openalex.org/I4210116723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124100291","display_name":"Dunzhao Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133355","display_name":"Jiangling Motors Corporation (China)","ror":"https://ror.org/03f4b7c94","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210133355"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dunzhao Wu","raw_affiliation_strings":["Jiangling Motors Corporation, Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangling Motors Corporation, Ltd","institution_ids":["https://openalex.org/I4210133355"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124086710","display_name":"Zhihua Nie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116723","display_name":"Robotics Research (United States)","ror":"https://ror.org/020w2fr77","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116723"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhihua Nie","raw_affiliation_strings":["Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,The College of Intelligent Robotics and Advanced Manufacturing,Shanghai,China,200433","institution_ids":["https://openalex.org/I4210116723"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.60909978,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6919","last_page":"6926"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7900999784469604,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7900999784469604,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.09430000185966492,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.014000000432133675,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.8964999914169312},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.6007999777793884},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5641999840736389},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5069000124931335},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.374099999666214},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3716000020503998}],"concepts":[{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.8964999914169312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7297000288963318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6482999920845032},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.6007999777793884},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5641999840736389},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5069000124931335},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.374099999666214},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3716000020503998},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.364300012588501},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3612000048160553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.3483000099658966},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.30809998512268066},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29899999499320984},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26840001344680786},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.26330000162124634}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11342704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.46836504340171814}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2779049072","https://openalex.org/W2963163009","https://openalex.org/W3025509063","https://openalex.org/W3130628155","https://openalex.org/W3151130473","https://openalex.org/W3204146347","https://openalex.org/W4312560592","https://openalex.org/W4312734855","https://openalex.org/W4312950730","https://openalex.org/W4313178187","https://openalex.org/W4319300717","https://openalex.org/W4321021726","https://openalex.org/W4323065842","https://openalex.org/W4366352791","https://openalex.org/W4386494539","https://openalex.org/W4389977645","https://openalex.org/W4393159321","https://openalex.org/W4394597072","https://openalex.org/W4401041662","https://openalex.org/W4402704563","https://openalex.org/W4406013233","https://openalex.org/W4406611165","https://openalex.org/W4414110758"],"related_works":[],"abstract_inverted_index":{"Efficient":[0],"feature":[1,49,105],"learning":[2],"is":[3,82,150],"considered":[4],"indispensable":[5],"for":[6,107,189],"maximizing":[7],"the":[8,57,168],"representation":[9],"of":[10,60,148,157,173],"scarce":[11],"information":[12,81],"in":[13,175,192],"tiny":[14,33,127,155,193],"datasets.":[15,34,194],"However,":[16],"existing":[17],"methods":[18],"are":[19,101],"often":[20],"unable":[21],"to":[22,72,111],"fully":[23],"exploit":[24,113],"local":[25,48,114,178],"features":[26,74],"and":[27,55,62,90,140,170,180,186],"contextual":[28],"dependencies":[29],"when":[30],"dealing":[31],"with":[32,135],"To":[35],"overcome":[36],"this":[37],"shortcoming,":[38],"a":[39,65,87,130,145,153,184],"Cross-Feature":[40],"Vision":[41],"Transformer":[42,99],"(CF-ViT)":[43],"was":[44,70,94],"proposed,":[45],"which":[46],"decouples":[47],"refinement":[50],"from":[51,75],"global":[52,181],"context":[53],"modeling":[54],"leverages":[56],"complementary":[58],"strengths":[59],"CNNs":[61],"Transformers.":[63],"Specifically,":[64],"Cross-Scale":[66],"Fusion":[67],"(CSF)":[68],"module":[69,93],"introduced":[71],"integrate":[73],"multiple":[76],"scales,":[77],"ensuring":[78],"that":[79,120],"cross-scale":[80],"globally":[83],"embedded.":[84],"In":[85],"addition,":[86],"Feature":[88],"Enhancement":[89],"Reorganization":[91],"(FER)":[92],"incorporated":[95],"into":[96,103],"CF-ViT,":[97],"whereby":[98],"outputs":[100],"reorganized":[102],"2D":[104],"maps":[106],"convolution-based":[108],"detail":[109],"enhancement":[110],"thoroughly":[112],"information.":[115],"Extensive":[116],"experiments":[117],"have":[118],"demonstrated":[119],"CF-ViT":[121,174],"consistently":[122],"surpasses":[123],"baselines":[124],"across":[125],"4":[126],"datasets,":[128],"reaching":[129],"96.87%":[131],"(KSDD)":[132],"Top-1":[133,146],"accuracy":[134,147],"only":[136],"29.19":[137],"million":[138],"parameters":[139],"2.67":[141],"billion":[142],"FLOPs.":[143],"Moreover,":[144],"85.03%":[149],"attained":[151],"on":[152],"real-world":[154],"dataset":[156],"wood":[158],"surface":[159],"defect":[160],"detection,":[161],"exceeding":[162],"all":[163],"baselines.":[164],"These":[165],"findings":[166],"underscore":[167],"effectiveness":[169],"generalization":[171],"capability":[172],"capturing":[176],"fine-grained":[177],"details":[179],"context,":[182],"offering":[183],"promising":[185],"deployable":[187],"solution":[188],"vision":[190],"tasks":[191]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-01-29T00:00:00"}