{"id":"https://openalex.org/W4408353903","doi":"https://doi.org/10.1109/icassp49660.2025.10887708","title":"Hybrid Feature Collaborative Reconstruction Network for Few-Shot Fine-Grained Image Classification","display_name":"Hybrid Feature Collaborative Reconstruction Network for Few-Shot Fine-Grained Image Classification","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408353903","doi":"https://doi.org/10.1109/icassp49660.2025.10887708"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10887708","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10887708","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5082215034","display_name":"Shulei Qiu","orcid":"https://orcid.org/0000-0003-0528-9651"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shulei Qiu","raw_affiliation_strings":["Nanjing Normal University Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Normal University Nanjing,China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078658353","display_name":"Wanqi Yang","orcid":"https://orcid.org/0000-0001-6727-6077"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanqi Yang","raw_affiliation_strings":["Nanjing Normal University Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Normal University Nanjing,China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034985240","display_name":"Ming Yang","orcid":"https://orcid.org/0009-0002-4952-1790"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Yang","raw_affiliation_strings":["Nanjing Normal University Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Normal University Nanjing,China","institution_ids":["https://openalex.org/I152031979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I152031979"],"apc_list":null,"apc_paid":null,"fwci":7.781,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.96510067,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.8823000192642212,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.8823000192642212,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.8456000089645386,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.8454999923706055,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7551310658454895},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.7144017815589905},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6343623995780945},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5812764167785645},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5200968980789185},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5129417777061462},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4965885281562805},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4708558917045593},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4518515467643738},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4344983398914337},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.10411632061004639}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7551310658454895},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.7144017815589905},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6343623995780945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5812764167785645},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5200968980789185},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5129417777061462},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4965885281562805},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4708558917045593},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4518515467643738},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4344983398914337},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.10411632061004639},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10887708","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10887708","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4300000071525574}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2138011018","https://openalex.org/W2462457117","https://openalex.org/W2737725206","https://openalex.org/W2957105406","https://openalex.org/W2964105864","https://openalex.org/W2965116998","https://openalex.org/W2965572487","https://openalex.org/W2979689312","https://openalex.org/W3005359536","https://openalex.org/W3012255272","https://openalex.org/W3107763055","https://openalex.org/W3130788242","https://openalex.org/W3176341011","https://openalex.org/W3177423475","https://openalex.org/W3187464273","https://openalex.org/W4304014288","https://openalex.org/W4312500832","https://openalex.org/W4376464610","https://openalex.org/W4382462216","https://openalex.org/W4385245566","https://openalex.org/W4386072314","https://openalex.org/W4389257994","https://openalex.org/W4391467957","https://openalex.org/W4393148571","https://openalex.org/W6638319203","https://openalex.org/W6717697761","https://openalex.org/W6758126075","https://openalex.org/W6766978945","https://openalex.org/W6770404601","https://openalex.org/W6783596713"],"related_works":["https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2980279061","https://openalex.org/W2334685461","https://openalex.org/W2366718574","https://openalex.org/W2359774528","https://openalex.org/W4298312966","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Our":[0],"research":[1],"focuses":[2],"on":[3,116],"few-shot":[4],"fine-grained":[5,17,120],"image":[6],"classification":[7],"(FS-FGIC),":[8],"which":[9],"faces":[10],"two":[11,58],"main":[12],"challenges:":[13],"the":[14,61,68,100,123],"similarity":[15],"of":[16,23,102,127],"objects":[18],"and":[19,35,67,85,104,110,125],"a":[20,50],"limited":[21,46],"number":[22],"samples.":[24,47],"Traditional":[25],"feature":[26],"reconstruction":[27,34,97],"networks":[28],"enhance":[29,82],"key":[30,59],"features":[31],"through":[32],"spatial":[33,83],"error":[36],"minimization":[37],"but":[38],"often":[39],"fail":[40],"to":[41,81,98],"capture":[42],"interclass":[43,109],"differences":[44],"with":[45,57],"We":[48],"propose":[49],"Hybrid":[51,62,69],"Feature":[52,63,70],"Collaborative":[53],"Reconstruction":[54,71],"Network":[55],"(HFCR-Net)":[56],"components:":[60],"Fusion":[64],"Process":[65,72],"(HFFP)":[66],"(HFRP).":[73],"In":[74,91],"HFRP,":[75,92],"dynamic":[76],"weight":[77],"adjustment":[78],"is":[79],"employed":[80],"dependencies":[84],"channel":[86,95],"correlations,":[87],"increasing":[88,108],"inter-class":[89],"differences.":[90,113],"we":[93],"introduce":[94],"dimension":[96],"improve":[99],"processes":[101],"support-to-query":[103],"query-to-support":[105],"reconstruction,":[106],"further":[107],"reducing":[111],"intra-class":[112],"Extensive":[114],"experiments":[115],"three":[117],"widely":[118],"used":[119],"datasets":[121],"confirm":[122],"effectiveness":[124],"superiority":[126],"our":[128],"approach.":[129]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
