{"id":"https://openalex.org/W4393085415","doi":"https://doi.org/10.1145/3653717","title":"Hierarchical Convolutional Neural Network with Knowledge Complementation for Long-Tailed Classification","display_name":"Hierarchical Convolutional Neural Network with Knowledge Complementation for Long-Tailed Classification","publication_year":2024,"publication_date":"2024-03-22","ids":{"openalex":"https://openalex.org/W4393085415","doi":"https://doi.org/10.1145/3653717"},"language":"en","primary_location":{"id":"doi:10.1145/3653717","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3653717","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3653717","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3653717","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058078141","display_name":"Hong Zhao","orcid":"https://orcid.org/0000-0001-9339-1829"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Minnan Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Zhao","raw_affiliation_strings":["Minnan Normal University,  Zhangzhou, China","School of Computer Science, Minnan Normal University","Key Laboratory of Data Science and Intelligence Application, Minnan Normal University, Zhangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9339-1829","affiliations":[{"raw_affiliation_string":"Minnan Normal University,  Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]},{"raw_affiliation_string":"School of Computer Science, Minnan Normal University","institution_ids":["https://openalex.org/I9356336"]},{"raw_affiliation_string":"Key Laboratory of Data Science and Intelligence Application, Minnan Normal University, Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106746424","display_name":"Zhengyu Li","orcid":"https://orcid.org/0000-0003-0548-254X"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Minnan Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyu Li","raw_affiliation_strings":["Minnan Normal University,  Zhangzhou, China","School of Computer Science, Minnan Normal University","Key Laboratory of Data Science and Intelligence Application, Minnan Normal University, Zhangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0548-254X","affiliations":[{"raw_affiliation_string":"Minnan Normal University,  Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]},{"raw_affiliation_string":"School of Computer Science, Minnan Normal University","institution_ids":["https://openalex.org/I9356336"]},{"raw_affiliation_string":"Key Laboratory of Data Science and Intelligence Application, Minnan Normal University, Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101583946","display_name":"Wenwei He","orcid":null},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Minnan Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenwei He","raw_affiliation_strings":["Minnan Normal University,  Zhangzhou, China","Key Laboratory of Data Science and Intelligence Application, Minnan Normal University, Zhangzhou, China","School of Computer Science, Minnan Normal University"],"raw_orcid":"https://orcid.org/0009-0000-7207-1594","affiliations":[{"raw_affiliation_string":"Minnan Normal University,  Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]},{"raw_affiliation_string":"Key Laboratory of Data Science and Intelligence Application, Minnan Normal University, Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]},{"raw_affiliation_string":"School of Computer Science, Minnan Normal University","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106743321","display_name":"Yan Zhao","orcid":"https://orcid.org/0009-0001-2295-7570"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Minnan Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Zhao","raw_affiliation_strings":["Minnan Normal University,  Zhangzhou China","School of Computer Science, Minnan Normal University"],"raw_orcid":"https://orcid.org/0009-0001-2295-7570","affiliations":[{"raw_affiliation_string":"Minnan Normal University,  Zhangzhou China","institution_ids":["https://openalex.org/I9356336"]},{"raw_affiliation_string":"School of Computer Science, Minnan Normal University","institution_ids":["https://openalex.org/I9356336"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0547,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.92079217,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"18","issue":"6","first_page":"1","last_page":"22"},"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":0.9995999932289124,"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":0.9995999932289124,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9990000128746033,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9958000183105469,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7369775772094727},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.719054639339447},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6860895752906799},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5736226439476013},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5463672876358032},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5048518776893616},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.4753672480583191},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.46157678961753845},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.44701823592185974},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.44442489743232727},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34847885370254517},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12415739893913269}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7369775772094727},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.719054639339447},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6860895752906799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5736226439476013},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5463672876358032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5048518776893616},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.4753672480583191},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.46157678961753845},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.44701823592185974},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.44442489743232727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34847885370254517},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12415739893913269},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3653717","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3653717","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3653717","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3653717","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3653717","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3653717","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5400000214576721}],"awards":[{"id":"https://openalex.org/G4907604791","display_name":null,"funder_award_id":"2021J011004","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G6275269864","display_name":null,"funder_award_id":"2021J011003","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G6716056982","display_name":null,"funder_award_id":"62376114","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7025034123","display_name":null,"funder_award_id":"2021J011003 and 2021J011004","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4393085415.pdf","grobid_xml":"https://content.openalex.org/works/W4393085415.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W126092743","https://openalex.org/W1977766639","https://openalex.org/W2017814585","https://openalex.org/W2074888575","https://openalex.org/W2082453965","https://openalex.org/W2101285851","https://openalex.org/W2108598243","https://openalex.org/W2115610681","https://openalex.org/W2117539524","https://openalex.org/W2185967890","https://openalex.org/W2194775991","https://openalex.org/W2440599146","https://openalex.org/W2534449155","https://openalex.org/W2612634114","https://openalex.org/W2621325907","https://openalex.org/W2797977484","https://openalex.org/W2908035133","https://openalex.org/W2962933664","https://openalex.org/W2963351448","https://openalex.org/W2963691377","https://openalex.org/W2991044292","https://openalex.org/W2997488121","https://openalex.org/W3011701287","https://openalex.org/W3034601242","https://openalex.org/W3034711780","https://openalex.org/W3035552357","https://openalex.org/W3038844667","https://openalex.org/W3041485444","https://openalex.org/W3115455310","https://openalex.org/W3172971995","https://openalex.org/W3174499303","https://openalex.org/W3174749609","https://openalex.org/W3176676637","https://openalex.org/W3179096061","https://openalex.org/W3182635745","https://openalex.org/W3186409582","https://openalex.org/W3191038157","https://openalex.org/W3197552003","https://openalex.org/W3210720059","https://openalex.org/W3214852842","https://openalex.org/W4200029748","https://openalex.org/W4200472276","https://openalex.org/W4200583727","https://openalex.org/W4205616158","https://openalex.org/W4298103743"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"Existing":[0],"methods":[1],"based":[2],"on":[3,150,174],"transfer":[4],"learning":[5],"leverage":[6],"auxiliary":[7,29,59],"information":[8,30,60,113],"to":[9,38,65,81,91,140,143],"help":[10],"tail":[11,19,32,40,66,141],"generalization":[12],"and":[13,31,34,61,72,107,136],"improve":[14,144],"the":[15,18,26,39,79,94,111,125,128,131,155,171,175],"performance":[16],"of":[17,97,130],"classes.":[20,41,67],"However,":[21],"they":[22],"cannot":[23],"fully":[24],"exploit":[25,93],"relationships":[27,57,74,135],"between":[28],"classes":[33],"bring":[35],"irrelevant":[36],"knowledge":[37,52,64,77,101,109,139],"To":[42],"solve":[43],"this":[44,123],"problem,":[45],"we":[46,69,86],"propose":[47],"a":[48,88,104],"hierarchical":[49,56,76,134],"CNN":[50,80,126],"with":[51,170],"complementation,":[53],"which":[54],"regards":[55],"as":[58,75,103],"transfers":[62,137],"relevant":[63],"First,":[68],"integrate":[70],"semantics":[71],"clustering":[73,108],"into":[78],"guide":[82],"feature":[83],"learning.":[84],"Then,":[85],"design":[87],"complementary":[89,133],"strategy":[90],"jointly":[92],"two":[95,132],"types":[96],"knowledge,":[98],"where":[99],"semantic":[100,117,120],"acts":[102],"prior":[105],"dependence":[106,118],"reduces":[110],"negative":[112],"caused":[114],"by":[115,167],"excessive":[116],"(i.e.,":[119],"gaps).":[121],"In":[122,161],"way,":[124],"facilitates":[127],"utilization":[129],"useful":[138],"data":[142],"long-tailed":[145,176],"classification":[146],"accuracy.":[147],"Experimental":[148],"results":[149],"public":[151],"benchmarks":[152],"show":[153],"that":[154],"proposed":[156],"model":[157,164],"outperforms":[158],"existing":[159],"methods.":[160],"particular,":[162],"our":[163],"improves":[165],"accuracy":[166],"3.46%":[168],"compared":[169],"second-best":[172],"method":[173],"tieredImageNet":[177],"dataset.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
