{"id":"https://openalex.org/W3171456465","doi":"https://doi.org/10.1109/icme51207.2021.9428148","title":"Knowledge Transfer Based Fine-Grained Visual Classification","display_name":"Knowledge Transfer Based Fine-Grained Visual Classification","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3171456465","doi":"https://doi.org/10.1109/icme51207.2021.9428148","mag":"3171456465"},"language":"en","primary_location":{"id":"doi:10.1109/icme51207.2021.9428148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme51207.2021.9428148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"article","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/A5016222863","display_name":"Siqing Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Siqing Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,The Pattern Recognition and Intelligent System Laboratory,Beijing,China","The Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,The Pattern Recognition and Intelligent System Laboratory,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"The Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011876517","display_name":"Ruoyi Du","orcid":"https://orcid.org/0000-0001-8372-5637"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruoyi Du","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,The Pattern Recognition and Intelligent System Laboratory,Beijing,China","The Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,The Pattern Recognition and Intelligent System Laboratory,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"The Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007417490","display_name":"Dongliang Chang","orcid":"https://orcid.org/0000-0002-4081-3001"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongliang Chang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,The Pattern Recognition and Intelligent System Laboratory,Beijing,China","The Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,The Pattern Recognition and Intelligent System Laboratory,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"The Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039812471","display_name":"Zhanyu Ma","orcid":"https://orcid.org/0000-0003-2950-2488"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanyu Ma","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,The Pattern Recognition and Intelligent System Laboratory,Beijing,China","The Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,The Pattern Recognition and Intelligent System Laboratory,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"The Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100445470","display_name":"Jun Guo","orcid":"https://orcid.org/0000-0001-9045-1339"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Guo","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,The Pattern Recognition and Intelligent System Laboratory,Beijing,China","The Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,The Pattern Recognition and Intelligent System Laboratory,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"The Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5016222863"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.748,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.74320242,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9970999956130981,"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":0.9970999956130981,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9952999949455261,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.995199978351593,"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/discriminative-model","display_name":"Discriminative model","score":0.93839430809021},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7563937902450562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6430160999298096},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5794757008552551},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5439507961273193},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5389296412467957},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4563591480255127},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.45281875133514404},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.41894763708114624},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41773441433906555},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4165400564670563},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4127589762210846}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.93839430809021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7563937902450562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6430160999298096},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5794757008552551},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5439507961273193},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5389296412467957},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4563591480255127},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.45281875133514404},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.41894763708114624},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41773441433906555},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4165400564670563},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4127589762210846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme51207.2021.9428148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme51207.2021.9428148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320326444","display_name":"Nova","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1690739335","https://openalex.org/W1797268635","https://openalex.org/W1821462560","https://openalex.org/W1836465849","https://openalex.org/W1846799578","https://openalex.org/W2117539524","https://openalex.org/W2118696714","https://openalex.org/W2138011018","https://openalex.org/W2561238782","https://openalex.org/W2737725206","https://openalex.org/W2740620254","https://openalex.org/W2773003563","https://openalex.org/W2780838211","https://openalex.org/W2798365843","https://openalex.org/W2891951760","https://openalex.org/W2917452308","https://openalex.org/W2950557962","https://openalex.org/W2963045696","https://openalex.org/W2963263347","https://openalex.org/W2963393555","https://openalex.org/W2963407932","https://openalex.org/W2964274719","https://openalex.org/W3008809756","https://openalex.org/W3009073662","https://openalex.org/W3028797339","https://openalex.org/W3108870912","https://openalex.org/W6637551013","https://openalex.org/W6638319203","https://openalex.org/W6638523607","https://openalex.org/W6638667902","https://openalex.org/W6638677478","https://openalex.org/W6726497184","https://openalex.org/W6730179637"],"related_works":["https://openalex.org/W3192840557","https://openalex.org/W3166467183","https://openalex.org/W3091976719","https://openalex.org/W4312417841","https://openalex.org/W3189091156","https://openalex.org/W2997709384","https://openalex.org/W4362564549","https://openalex.org/W4366224123","https://openalex.org/W3165266428","https://openalex.org/W2738221750"],"abstract_inverted_index":{"Fine-grained":[0],"visual":[1],"classification":[2],"(FGVC)":[3],"aims":[4],"to":[5,18,62,90,124,139,143],"distinguish":[6],"the":[7,10,20,31,37,44,49,84,126,129,141,151,170,176,179],"sub-classes":[8],"of":[9,80,128,178],"same":[11],"category":[12],"and":[13,22,53,114,146,182],"its":[14],"essential":[15],"solution":[16],"is":[17,137,154],"mine":[19],"subtle":[21],"discriminative":[23,51,69,93],"regions.":[24,57,94,148],"Convolution":[25],"neural":[26],"networks":[27],"(CNNs),":[28],"which":[29],"employ":[30],"cross":[32],"entropy":[33],"loss":[34,38,135],"(CE-loss)":[35],"as":[36,121],"function,":[39],"show":[40],"poor":[41],"performance":[42],"since":[43],"model":[45,153],"can":[46],"only":[47,157],"learn":[48],"most":[50,79],"part":[52],"ignore":[54],"other":[55],"meaningful":[56,147],"Some":[58],"existing":[59],"works":[60],"try":[61],"solve":[63],"this":[64,96],"problem":[65,87],"by":[66,71,112],"mining":[67],"more":[68,92],"regions":[70],"some":[72],"detection":[73],"techniques":[74],"or":[75],"attention":[76],"mechanisms.":[77],"However,":[78],"them":[81],"will":[82],"meet":[83],"background":[85],"noise":[86],"when":[88],"trying":[89],"find":[91,144],"In":[95,149],"paper,":[97],"we":[98],"address":[99],"it":[100],"in":[101],"a":[102,133],"knowledge":[103,165],"transfer":[104],"learning":[105],"manner.":[106],"Multiple":[107],"models":[108,118,123],"are":[109,119,166],"trained":[110,117,155],"one":[111],"one,":[113],"all":[115,160],"previously":[116],"regarded":[120],"teacher":[122],"supervise":[125],"training":[127],"current":[130],"one.":[131],"Specifically,":[132],"orthogonal":[134],"(OR-loss)":[136],"proposed":[138,180],"encourage":[140],"network":[142],"diverse":[145],"addition,":[150],"first":[152],"with":[156,163],"CE-Loss.":[158],"Finally,":[159],"models\u2019":[161],"outputs":[162],"complementary":[164],"combined":[167],"together":[168],"for":[169],"final":[171],"prediction":[172],"result.":[173],"We":[174],"demonstrate":[175],"superiority":[177],"method":[181],"obtain":[183],"state-of-the-art":[184],"(SOTA)":[185],"performances":[186],"on":[187],"three":[188],"popular":[189],"FGVC":[190],"datasets.":[191]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}