{"id":"https://openalex.org/W7155099774","doi":"https://doi.org/10.48550/arxiv.2604.16936","title":"Adaptive receptive field-based spatial-frequency feature reconstruction network for few-shot fine-grained image classification","display_name":"Adaptive receptive field-based spatial-frequency feature reconstruction network for few-shot fine-grained image classification","publication_year":2026,"publication_date":"2026-04-18","ids":{"openalex":"https://openalex.org/W7155099774","doi":"https://doi.org/10.48550/arxiv.2604.16936"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.16936","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16936","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.2604.16936","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045379992","display_name":"Linyue Zhang","orcid":"https://orcid.org/0000-0002-0623-4727"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Linyue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101952555","display_name":"Wenyi Zeng","orcid":"https://orcid.org/0000-0002-8699-2738"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Wenyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134159780","display_name":"Zicheng Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Zicheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134203443","display_name":"Yongsheng Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Yongsheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134117423","display_name":"Changming Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Changming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134192171","display_name":"Jun Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Jun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134133384","display_name":"Lixian Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Lixian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134174230","display_name":"Weichuan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Weichuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134199588","display_name":"Tuo Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Tuo","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":0.5953999757766724,"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":0.5953999757766724,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.08619999885559082,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.019899999722838402,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/feature","display_name":"Feature (linguistics)","score":0.743399977684021},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6855000257492065},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5972999930381775},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5346999764442444},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5177000164985657},{"id":"https://openalex.org/keywords/receptive-field","display_name":"Receptive field","score":0.48080000281333923},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4113999903202057}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.776199996471405},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.743399977684021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7232999801635742},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6855000257492065},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5972999930381775},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5346999764442444},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5177000164985657},{"id":"https://openalex.org/C19071747","wikidata":"https://www.wikidata.org/wiki/Q1755207","display_name":"Receptive field","level":2,"score":0.48080000281333923},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4465000033378601},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4113999903202057},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3508000075817108},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3481000065803528},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3418000042438507},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28189998865127563},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.2784000039100647},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.272599995136261}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.16936","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16936","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.2604.16936","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16936","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":{"Feature":[0],"reconstruction":[1,66,94],"techniques":[2],"are":[3],"widely":[4],"applied":[5],"for":[6,83,93,111],"few-shot":[7],"fine-grained":[8],"image":[9],"classification":[10],"(FSFGIC).":[11],"Our":[12],"research":[13],"indicates":[14],"that":[15],"one":[16],"of":[17,32,127],"the":[18,30,33,54,75,123,128],"main":[19],"challenges":[20],"facing":[21],"existing":[22],"feature-based":[23],"FSFGIC":[24,55,96,120],"methods":[25],"is":[26,69,136],"how":[27],"to":[28,36,77],"choose":[29],"size":[31],"receptive":[34,62,80],"field":[35,81],"extract":[37],"feature":[38,44,65],"descriptors":[39],"(including":[40],"spatial":[41,85],"and":[42,86,89,95,125],"frequency":[43,87],"descriptors)":[45],"from":[46,114],"different":[47],"category":[48],"input":[49],"images,":[50],"thereby":[51],"better":[52],"performing":[53],"tasks.":[56,97],"To":[57],"address":[58],"this,":[59],"an":[60],"adaptive":[61],"field-based":[63],"spatial-frequency":[64],"network":[67],"(ARF-SFR-Net)":[68],"proposed.":[70],"The":[71,98,134],"designed":[72,99],"ARF-SFR-Net":[73,100,130],"has":[74],"capability":[76],"adaptively":[78],"determine":[79],"sizes":[82],"obtaining":[84],"features,":[88],"effectively":[90],"fuse":[91],"them":[92],"can":[101],"be":[102],"easily":[103],"embedded":[104],"into":[105],"a":[106],"given":[107],"episodic":[108],"training":[109,113],"mechanism":[110],"end-to-end":[112],"scratch.":[115],"Extensive":[116],"experiments":[117],"on":[118],"multiple":[119],"benchmarks":[121],"demonstrate":[122],"effectiveness":[124],"superiority":[126],"proposed":[129],"over":[131],"state-of-the-art":[132],"approaches.":[133],"code":[135],"available":[137],"at:":[138],"https://github.com/ICL-SUST/ARF-SFR-Net.git.":[139]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-22T00:00:00"}
