{"id":"https://openalex.org/W3166770553","doi":"https://doi.org/10.1109/icme51207.2021.9428421","title":"Intra-Class Uncertainty Loss Function For Classification","display_name":"Intra-Class Uncertainty Loss Function For Classification","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3166770553","doi":"https://doi.org/10.1109/icme51207.2021.9428421","mag":"3166770553"},"language":"en","primary_location":{"id":"doi:10.1109/icme51207.2021.9428421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme51207.2021.9428421","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":"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/A5101566415","display_name":"He Zhu","orcid":"https://orcid.org/0000-0002-1008-7774"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Zhu","raw_affiliation_strings":["Chinese Academy of Sciences(CASIA),Brainnetome Center, National Laboratory of Pattern Recognition (NLPR), Institute of Automation","School of Future Technology, University of Chinese Academy of Sciences(UCAS)","Brainnetome Center, National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences(CASIA)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences(CASIA),Brainnetome Center, National Laboratory of Pattern Recognition (NLPR), Institute of Automation","institution_ids":["https://openalex.org/I4210112150"]},{"raw_affiliation_string":"School of Future Technology, University of Chinese Academy of Sciences(UCAS)","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Brainnetome Center, National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences(CASIA)","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100759691","display_name":"Shan Yu","orcid":"https://orcid.org/0000-0002-9008-6658"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210097554","display_name":"Center for Excellence in Brain Science and Intelligence Technology","ror":"https://ror.org/00vpwhm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210097554"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Yu","raw_affiliation_strings":["Chinese Academy of Sciences(CASIA),Brainnetome Center, National Laboratory of Pattern Recognition (NLPR), Institute of Automation","School of Future Technology, University of Chinese Academy of Sciences(UCAS)","Brainnetome Center, National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences(CASIA)","CAS Center for Excellence, Brain Science and Intelligence Technology(CEBSIT)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences(CASIA),Brainnetome Center, National Laboratory of Pattern Recognition (NLPR), Institute of Automation","institution_ids":["https://openalex.org/I4210112150"]},{"raw_affiliation_string":"School of Future Technology, University of Chinese Academy of Sciences(UCAS)","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Brainnetome Center, National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences(CASIA)","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"CAS Center for Excellence, Brain Science and Intelligence Technology(CEBSIT)","institution_ids":["https://openalex.org/I4210097554"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"141","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":0.9994999766349792,"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":0.9994999766349792,"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":0.9993000030517578,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6992201209068298},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6742737889289856},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6205089092254639},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5863569974899292},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5730905532836914},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5545731782913208},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4858989119529724},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.48360127210617065},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4499064087867737},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4412151873111725},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4173046350479126},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37962543964385986},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32835614681243896},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3282284736633301}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6992201209068298},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6742737889289856},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6205089092254639},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5863569974899292},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5730905532836914},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5545731782913208},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4858989119529724},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.48360127210617065},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4499064087867737},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4412151873111725},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4173046350479126},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37962543964385986},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32835614681243896},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3282284736633301},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme51207.2021.9428421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme51207.2021.9428421","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2096733369","https://openalex.org/W2138621090","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2520774990","https://openalex.org/W2609575245","https://openalex.org/W2765407302","https://openalex.org/W2784163702","https://openalex.org/W2784293261","https://openalex.org/W2950800384","https://openalex.org/W2962677013","https://openalex.org/W2962898354","https://openalex.org/W2962922273","https://openalex.org/W2963166243","https://openalex.org/W2963314614","https://openalex.org/W2963351448","https://openalex.org/W2963466847","https://openalex.org/W2963656735","https://openalex.org/W2963691377","https://openalex.org/W2964213180","https://openalex.org/W2965798135","https://openalex.org/W2981958729","https://openalex.org/W2984006054","https://openalex.org/W3101227480","https://openalex.org/W3103152812","https://openalex.org/W6620707391","https://openalex.org/W6684191040","https://openalex.org/W6714138976","https://openalex.org/W6735013348","https://openalex.org/W6736780073","https://openalex.org/W6745136726","https://openalex.org/W6747583068","https://openalex.org/W6748257384"],"related_works":["https://openalex.org/W2950475743","https://openalex.org/W4386603768","https://openalex.org/W2886711096","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W2590796488","https://openalex.org/W4389249638","https://openalex.org/W2734358244","https://openalex.org/W2169866437","https://openalex.org/W1964286703"],"abstract_inverted_index":{"Most":[0],"classification":[1,29,153],"models":[2],"can":[3],"be":[4],"considered":[5],"as":[6,89],"the":[7,50,83,90,97,100,109,131,148],"process":[8],"of":[9,56,67,82,102,133],"matching":[10],"templates.":[11],"However,":[12],"when":[13],"intra-class":[14,41,121],"uncertainty/variability":[15],"is":[16],"not":[17],"considered,":[18],"especially":[19],"for":[20],"datasets":[21],"containing":[22],"unbalanced":[23],"classes,":[24],"this":[25,33],"may":[26],"lead":[27],"to":[28,108,120,123],"errors.":[30],"To":[31],"address":[32],"issue,":[34],"we":[35,116],"propose":[36],"a":[37,72,86,118,157],"loss":[38,114],"function":[39],"with":[40,71,76],"uncertainty":[42,101,122],"following":[43],"Gaussian":[44,63,84],"distribution.":[45,64],"Specifically,":[46],"in":[47,93,112],"our":[48],"framework,":[49],"features":[51],"extracted":[52],"by":[53,61],"deep":[54],"networks":[55],"each":[57,125],"class":[58,159],"are":[59,69],"characterized":[60],"independent":[62],"The":[65,80],"parameters":[66],"distribution":[68,135],"learned":[70],"likelihood":[73],"regularization":[74],"along":[75],"other":[77],"network":[78],"parameters.":[79],"means":[81],"play":[85],"similar":[87,107],"role":[88],"center":[91],"anchor":[92],"existing":[94],"methods,":[95],"and":[96,129,144],"variance":[98],"describes":[99],"different":[103,137],"classes.":[104],"In":[105],"addition,":[106],"inter-class":[110],"margin":[111,119],"traditional":[113],"functions,":[115],"introduce":[117],"make":[124],"cluster":[126],"more":[127],"compact":[128],"reduce":[130],"imbalance":[132],"feature":[134],"from":[136],"categories.":[138],"Based":[139],"on":[140],"MNIST,":[141],"CIFAR,":[142],"ImageNet,":[143],"Long-tailed":[145],"CIFAR":[146],"analyses,":[147],"proposed":[149],"approach":[150],"shows":[151],"improved":[152],"performance,":[154],"through":[155],"learning":[156],"better":[158],"representation.":[160]},"counts_by_year":[{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2025-10-10T00:00:00"}