{"id":"https://openalex.org/W3034572110","doi":"https://doi.org/10.1109/icme46284.2020.9102809","title":"Knowledge-Based Fine-Grained Classification For Few-Shot Learning","display_name":"Knowledge-Based Fine-Grained Classification For Few-Shot Learning","publication_year":2020,"publication_date":"2020-06-09","ids":{"openalex":"https://openalex.org/W3034572110","doi":"https://doi.org/10.1109/icme46284.2020.9102809","mag":"3034572110"},"language":"en","primary_location":{"id":"doi:10.1109/icme46284.2020.9102809","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102809","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","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/A5101554229","display_name":"Jiabao Zhao","orcid":"https://orcid.org/0000-0002-0691-5741"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiabao Zhao","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100398281","display_name":"Xin Lin","orcid":"https://orcid.org/0000-0001-6913-4654"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Lin","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100770462","display_name":"Jie Zhou","orcid":"https://orcid.org/0000-0002-2589-0164"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhou","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100704226","display_name":"Jing Yang","orcid":"https://orcid.org/0000-0002-0315-1686"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Yang","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010540039","display_name":"Liang He","orcid":"https://orcid.org/0000-0002-4723-5486"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang He","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000095574","display_name":"Zhaohui Yang","orcid":"https://orcid.org/0000-0003-1105-8841"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhaohui Yang","raw_affiliation_strings":["Insigma Hengtian Software Ltd., Hangzhou, Zhejiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Insigma Hengtian Software Ltd., Hangzhou, Zhejiang, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9991000294685364,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9649999737739563,"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":0.8445438146591187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6677496433258057},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.577401340007782},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5633584856987},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5068326592445374},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.4830484986305237},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4767913818359375},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42341285943984985},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42149415612220764},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40728944540023804},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3019701838493347},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.08407825231552124}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8445438146591187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6677496433258057},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.577401340007782},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5633584856987},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5068326592445374},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.4830484986305237},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4767913818359375},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42341285943984985},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42149415612220764},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40728944540023804},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3019701838493347},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.08407825231552124},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme46284.2020.9102809","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102809","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1527575280","https://openalex.org/W1797268635","https://openalex.org/W2138011018","https://openalex.org/W2250539671","https://openalex.org/W2398118205","https://openalex.org/W2552579943","https://openalex.org/W2601450892","https://openalex.org/W2604763608","https://openalex.org/W2787705367","https://openalex.org/W2797488484","https://openalex.org/W2798836702","https://openalex.org/W2808498263","https://openalex.org/W2893749619","https://openalex.org/W2928798948","https://openalex.org/W2947087054","https://openalex.org/W2952716587","https://openalex.org/W2961018736","https://openalex.org/W2963341924","https://openalex.org/W2963636184","https://openalex.org/W2964105864","https://openalex.org/W2964249870","https://openalex.org/W2982247743","https://openalex.org/W3105338408","https://openalex.org/W4293412117","https://openalex.org/W6631516269","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6748555532","https://openalex.org/W6750736493","https://openalex.org/W6750782335","https://openalex.org/W6752940074","https://openalex.org/W6755312952","https://openalex.org/W6762981687"],"related_works":["https://openalex.org/W1982774199","https://openalex.org/W2026121273","https://openalex.org/W1914651075","https://openalex.org/W2773500201","https://openalex.org/W2776636865","https://openalex.org/W2126384842","https://openalex.org/W1979068194","https://openalex.org/W1835905048","https://openalex.org/W2541950815","https://openalex.org/W2112343299"],"abstract_inverted_index":{"The":[0,30],"small":[1],"inter-class":[2],"variance":[3,8],"and":[4,12,36,93,104,111,118],"the":[5,10,19,39,56,67,87,101,105,123,128,145,149,164],"large":[6],"intra-class":[7],"make":[9],"few-shot":[11,49,82],"fine-grained":[13,78],"image":[14],"classification":[15,79],"more":[16,34],"difficult":[17],"because":[18],"machine":[20],"cannot":[21],"obtain":[22],"enough":[23],"information":[24],"from":[25,59,96,108],"only":[26,52,90],"a":[27,76,112,135],"few":[28],"images.":[29],"external":[31,69],"knowledge":[32,106,114],"contains":[33],"semantics":[35],"can":[37,85],"support":[38],"model":[40],"to":[41,66,121,143],"extract":[42,100],"important":[43],"features,":[44,132],"while":[45],"most":[46],"of":[47,89],"existing":[48],"learning":[50],"algorithms":[51],"focus":[53],"on":[54],"leveraging":[55],"visual":[57,102],"features":[58,95,103,107,147],"images,":[60],"little":[61],"attention":[62],"has":[63],"been":[64],"paid":[65],"cross-modal":[68],"knowledge.":[70],"In":[71],"this":[72],"paper,":[73],"we":[74,133],"propose":[75,134],"knowledge-based":[77],"mechanism":[80],"for":[81],"learning,":[83],"which":[84],"overcome":[86],"difficulty":[88],"obtaining":[91],"limited":[92],"discriminative":[94],"unimodal":[97],"samples.":[98],"We":[99],"textual":[109],"descriptions":[110],"domain-specific":[113],"graph":[115],"at":[116],"global":[117],"local":[119],"levels":[120],"build":[122],"semantic":[124,151],"space.":[125],"To":[126],"tackle":[127],"gap":[129],"between":[130],"multimodal":[131,146],"mirror":[136],"framework,":[137],"named":[138],"Mirror":[139],"Mapping":[140],"Network":[141],"(MMN),":[142],"map":[144],"into":[148],"same":[150],"space":[152],"with":[153],"two":[154],"directions.":[155],"Extensive":[156],"experimental":[157],"results":[158],"show":[159],"that":[160],"our":[161],"method":[162],"outperforms":[163],"state-of-the-art.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}