{"id":"https://openalex.org/W3161651176","doi":"https://doi.org/10.1109/icpr48806.2021.9412634","title":"Multi-Attribute Learning With Highly Imbalanced Data","display_name":"Multi-Attribute Learning With Highly Imbalanced Data","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3161651176","doi":"https://doi.org/10.1109/icpr48806.2021.9412634","mag":"3161651176"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412634","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412634","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5108905292","display_name":"Lady Viviana Beltr\u00e1n Beltr\u00e1n","orcid":null},"institutions":[{"id":"https://openalex.org/I78744979","display_name":"La Rochelle Universit\u00e9","ror":"https://ror.org/04mv1z119","country_code":"FR","type":"education","lineage":["https://openalex.org/I78744979"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"L. Viviana Beltran Beltran","raw_affiliation_strings":["University of La Rochelle, France"],"affiliations":[{"raw_affiliation_string":"University of La Rochelle, France","institution_ids":["https://openalex.org/I78744979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063992777","display_name":"Micka\u00ebl Coustaty","orcid":"https://orcid.org/0000-0002-0123-439X"},"institutions":[{"id":"https://openalex.org/I78744979","display_name":"La Rochelle Universit\u00e9","ror":"https://ror.org/04mv1z119","country_code":"FR","type":"education","lineage":["https://openalex.org/I78744979"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mickael Coustaty","raw_affiliation_strings":["University of La Rochelle, France"],"affiliations":[{"raw_affiliation_string":"University of La Rochelle, France","institution_ids":["https://openalex.org/I78744979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068432538","display_name":"Nicholas Journet","orcid":"https://orcid.org/0000-0002-6773-4071"},"institutions":[{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nicholas Journet","raw_affiliation_strings":["University of Bordeaux, France"],"affiliations":[{"raw_affiliation_string":"University of Bordeaux, France","institution_ids":["https://openalex.org/I15057530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030361802","display_name":"Juan Carlos Caicedo","orcid":"https://orcid.org/0000-0003-3936-6395"},"institutions":[{"id":"https://openalex.org/I107606265","display_name":"Broad Institute","ror":"https://ror.org/05a0ya142","country_code":"US","type":"funder","lineage":["https://openalex.org/I107606265"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Juan C. Caicedo","raw_affiliation_strings":["Broad Institute of MIT and Harvard, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Broad Institute of MIT and Harvard, Cambridge, MA, USA","institution_ids":["https://openalex.org/I107606265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033491986","display_name":"Antoine Doucet","orcid":"https://orcid.org/0000-0001-6160-3356"},"institutions":[{"id":"https://openalex.org/I78744979","display_name":"La Rochelle Universit\u00e9","ror":"https://ror.org/04mv1z119","country_code":"FR","type":"education","lineage":["https://openalex.org/I78744979"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Antoine Doucet","raw_affiliation_strings":["University of La Rochelle, France"],"affiliations":[{"raw_affiliation_string":"University of La Rochelle, France","institution_ids":["https://openalex.org/I78744979"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5108905292"],"corresponding_institution_ids":["https://openalex.org/I78744979"],"apc_list":null,"apc_paid":null,"fwci":0.2719,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61400956,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998000264167786,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998000264167786,"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":0.9969000220298767,"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/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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":0.8235002160072327},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6969859004020691},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6331256628036499},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6324156522750854},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5946055054664612},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5540400147438049},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5397738814353943},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5226894617080688},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.44150039553642273}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8235002160072327},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6969859004020691},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6331256628036499},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6324156522750854},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5946055054664612},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5540400147438049},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5397738814353943},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5226894617080688},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.44150039553642273},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412634","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412634","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1589462096","https://openalex.org/W1618905105","https://openalex.org/W1797268635","https://openalex.org/W1834627138","https://openalex.org/W2052684427","https://openalex.org/W2109317801","https://openalex.org/W2114354594","https://openalex.org/W2124940540","https://openalex.org/W2125560515","https://openalex.org/W2147414309","https://openalex.org/W2194775991","https://openalex.org/W2440599146","https://openalex.org/W2551429935","https://openalex.org/W2562319768","https://openalex.org/W2604968786","https://openalex.org/W2748618181","https://openalex.org/W2752539069","https://openalex.org/W2775447965","https://openalex.org/W2794284562","https://openalex.org/W2806857802","https://openalex.org/W2867270703","https://openalex.org/W2911964244","https://openalex.org/W2962843773","https://openalex.org/W2963212406","https://openalex.org/W2963351448","https://openalex.org/W2963465381","https://openalex.org/W2963566126","https://openalex.org/W2963691377","https://openalex.org/W2963725249","https://openalex.org/W2963960318","https://openalex.org/W2969882485","https://openalex.org/W2981361036","https://openalex.org/W3003800279","https://openalex.org/W3010512657","https://openalex.org/W3012948168","https://openalex.org/W3013664915","https://openalex.org/W3015045658","https://openalex.org/W3035367622","https://openalex.org/W3035590987","https://openalex.org/W3035607448","https://openalex.org/W3035655772","https://openalex.org/W4225596656","https://openalex.org/W4287824352","https://openalex.org/W4288254513","https://openalex.org/W6635220818","https://openalex.org/W6636501900","https://openalex.org/W6678800043","https://openalex.org/W6712236487","https://openalex.org/W6736057215","https://openalex.org/W6775621247"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2997567050","https://openalex.org/W2397288865","https://openalex.org/W2611989081","https://openalex.org/W1483272040","https://openalex.org/W4283377908","https://openalex.org/W2368524271","https://openalex.org/W1533421371","https://openalex.org/W4247116873","https://openalex.org/W2576709312"],"abstract_inverted_index":{"Data":[0],"is":[1,124,194],"one":[2,120,131],"of":[3,21,58,66,98,121,132,200,203,209,238,245,255,270,276,312],"the":[4,19,53,67,74,89,133,171,175,179,198,201,253,268,271,310,313],"most":[5,65],"important":[6],"keys":[7,80],"for":[8,154,303],"success":[9],"when":[10,41,91,108],"studying":[11],"a":[12,15,92,125,290],"simple":[13],"or":[14,116],"complex":[16,36],"phenomenon.":[17],"With":[18],"use":[20,34,208,221],"deep":[22,37,111,148,278],"learning":[23,38,102,112,149,249,279],"exploding":[24],"and":[25,55,235,302,305],"its":[26,225],"democratization,":[27],"non-computer":[28],"science":[29],"experts":[30],"may":[31],"struggle":[32],"to":[33,73,86,128,144,187,224,263],"highly":[35],"architectures,":[39],"even":[40],"straightforward":[42,147],"models":[43,150,157],"offer":[44],"them":[45,239],"suitable":[46],"performances.":[47],"In":[48],"this":[49],"article,":[50],"we":[51,83,139,177,298],"study":[52],"specific":[54],"common":[56],"problem":[57],"data":[59,75,93],"imbalance":[60],"in":[61,169,197,252,286],"real":[62],"databases":[63],"as":[64,161,190,218],"bad":[68],"performance":[69,287],"problems":[70,134],"are":[71,167,185],"due":[72,223],"itself.":[76],"We":[77,206,281],"cover":[78],"two":[79,231],"aspects.":[81],"First,":[82],"propose":[84],"ways":[85],"deal":[87],"with":[88,142,230],"situation":[90],"set":[94],"contains":[95],"different":[96],"levels":[97],"imbalance.":[99,137],"Classical":[100],"imbalanced":[101,227],"strategies":[103,259,308],"cannot":[104],"be":[105,159],"directly":[106],"applied":[107],"using":[109,289],"multi-attribute":[110,241,277],"models,":[113],"i.e.,":[114],"multi-task":[115],"multi-label":[117],"architectures.":[118],"Therefore,":[119],"our":[122,219,257,307],"contributions":[123],"proposed":[126,258],"adaptation":[127],"face":[129],"each":[130],"derived":[135],"from":[136],"Second,":[138],"demonstrate":[140,250],"that":[141,184,251],"little":[143],"no":[145],"imbalance,":[146,256],"work":[151],"well.":[152],"However,":[153],"non-experts,":[155],"these":[156],"can":[158],"seen":[160],"black":[162],"boxes,":[163],"where":[164],"all":[165],"efforts":[166],"invested":[168],"preprocessing":[170],"data.":[172],"To":[173],"simplify":[174],"problem,":[176],"perform":[178],"classification":[180],"task":[181],"without":[182],"features":[183],"costly":[186],"extract,":[188],"such":[189],"part":[191],"localization":[192],"which":[193],"widely":[195,211],"used":[196],"state":[199,269,311],"art":[202,272],"attribute":[204,213,248],"classification.":[205],"make":[207,260],"three":[210],"known":[212],"databases,":[214],"CUB-200-2011":[215],"-":[216],"CUB":[217],"main":[220],"case":[222],"deeply":[226],"nature,":[228],"along":[229],"balanced":[232],"databases:":[233],"celebA":[234],"AwA2.":[236],"All":[237],"contain":[240],"annotations.":[242],"The":[243],"results":[244,266],"very":[246],"fine-grained":[247],"presence":[254],"it":[261],"possible":[262],"have":[264,299],"competitive":[265,300],"against":[267],"while":[273,288],"taking":[274],"advantage":[275],"models.":[280],"also":[282],"noticed":[283],"an":[284],"increase":[285],"specialized":[291],"loss":[292],"function":[293],"(Focal":[294],"Loss).":[295],"For":[296],"CUB,":[297],"results,":[301],"CelebA":[304],"AwA2":[306],"over-perform":[309],"art.":[314]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}