{"id":"https://openalex.org/W3179856907","doi":"https://doi.org/10.1109/tip.2021.3094744","title":"BiSPL: Bidirectional Self-Paced Learning for Recognition From Web Data","display_name":"BiSPL: Bidirectional Self-Paced Learning for Recognition From Web Data","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3179856907","doi":"https://doi.org/10.1109/tip.2021.3094744","mag":"3179856907","pmid":"https://pubmed.ncbi.nlm.nih.gov/34252026"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2021.3094744","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3094744","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101891970","display_name":"Xiaoping Wu","orcid":"https://orcid.org/0000-0002-3067-4626"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoping Wu","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038083485","display_name":"Jianlong Chang","orcid":"https://orcid.org/0000-0002-0610-907X"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianlong Chang","raw_affiliation_strings":["Huawei Cloud & AI, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Cloud & AI, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067850699","display_name":"Yu\u2010Kun Lai","orcid":"https://orcid.org/0000-0002-2094-5680"},"institutions":[{"id":"https://openalex.org/I79510175","display_name":"Cardiff University","ror":"https://ror.org/03kk7td41","country_code":"GB","type":"education","lineage":["https://openalex.org/I79510175"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yu-Kun Lai","raw_affiliation_strings":["School of Computer Science and Informatics, Cardiff University, Cardiff, U.K"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Informatics, Cardiff University, Cardiff, U.K","institution_ids":["https://openalex.org/I79510175"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089409678","display_name":"Jufeng Yang","orcid":"https://orcid.org/0000-0003-0219-3443"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jufeng Yang","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100393506","display_name":"Qi Tian","orcid":"https://orcid.org/0000-0002-7252-5047"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Tian","raw_affiliation_strings":["Huawei Cloud & AI, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Cloud & AI, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101891970"],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":0.9797,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.8050922,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"30","issue":null,"first_page":"6512","last_page":"6527"},"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":0.9994000196456909,"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":0.9994000196456909,"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":0.9884999990463257,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9851999878883362,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7940897345542908},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.724844217300415},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6721516251564026},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6011756658554077},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5941001176834106},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5476202368736267},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5261880159378052},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4790983498096466},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.47084519267082214},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.44497501850128174},{"id":"https://openalex.org/keywords/web-application","display_name":"Web application","score":0.434080570936203},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.42741984128952026},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36088114976882935},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34182554483413696},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2349904477596283},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.09502807259559631}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7940897345542908},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.724844217300415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6721516251564026},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6011756658554077},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5941001176834106},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5476202368736267},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5261880159378052},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4790983498096466},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.47084519267082214},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.44497501850128174},{"id":"https://openalex.org/C118643609","wikidata":"https://www.wikidata.org/wiki/Q189210","display_name":"Web application","level":2,"score":0.434080570936203},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.42741984128952026},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36088114976882935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34182554483413696},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2349904477596283},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.09502807259559631},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tip.2021.3094744","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3094744","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:34252026","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34252026","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:http://orca.cardiff.ac.uk:143075","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401195","display_name":"ORCA Online Research @Cardiff (Cardiff University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79510175","host_organization_name":"Cardiff University","host_organization_lineage":["https://openalex.org/I79510175"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:http://orca-dev.cardiff.ac.uk:143075","is_oa":false,"landing_page_url":"https://orca.cardiff.ac.uk/id/eprint/143075/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401195","display_name":"ORCA Online Research @Cardiff (Cardiff University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79510175","host_organization_name":"Cardiff University","host_organization_lineage":["https://openalex.org/I79510175"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1729323816","display_name":null,"funder_award_id":"20JCJQJC00020","funder_id":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City"},{"id":"https://openalex.org/G4620801591","display_name":null,"funder_award_id":"61876094","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5884194724","display_name":null,"funder_award_id":"18JCYBJC15400","funder_id":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City"},{"id":"https://openalex.org/G6290357695","display_name":null,"funder_award_id":"2018AAA0100403","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6866399467","display_name":null,"funder_award_id":"18ZXZNGX00110","funder_id":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City"},{"id":"https://openalex.org/G8876575766","display_name":null,"funder_award_id":"U1933114","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323993","display_name":"Natural Science Foundation of Tianjin City","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":143,"referenced_works":["https://openalex.org/W12634471","https://openalex.org/W56385144","https://openalex.org/W639708223","https://openalex.org/W1797268635","https://openalex.org/W1898560071","https://openalex.org/W1924160326","https://openalex.org/W1932481952","https://openalex.org/W1964763677","https://openalex.org/W1995137594","https://openalex.org/W2117539524","https://openalex.org/W2132984949","https://openalex.org/W2134670479","https://openalex.org/W2136951832","https://openalex.org/W2147483361","https://openalex.org/W2152161678","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2206370378","https://openalex.org/W2207849498","https://openalex.org/W2229419338","https://openalex.org/W2287418003","https://openalex.org/W2289708887","https://openalex.org/W2289772031","https://openalex.org/W2296073425","https://openalex.org/W2321533354","https://openalex.org/W2326925005","https://openalex.org/W2358876993","https://openalex.org/W2401239971","https://openalex.org/W2469228190","https://openalex.org/W2475223347","https://openalex.org/W2513667154","https://openalex.org/W2514167171","https://openalex.org/W2519887557","https://openalex.org/W2530422462","https://openalex.org/W2533598788","https://openalex.org/W2555741539","https://openalex.org/W2555897561","https://openalex.org/W2557912764","https://openalex.org/W2585858557","https://openalex.org/W2592335154","https://openalex.org/W2604924528","https://openalex.org/W2613718673","https://openalex.org/W2620239873","https://openalex.org/W2731821979","https://openalex.org/W2732026016","https://openalex.org/W2742318416","https://openalex.org/W2746314669","https://openalex.org/W2752782242","https://openalex.org/W2752971446","https://openalex.org/W2770456481","https://openalex.org/W2773003563","https://openalex.org/W2798381792","https://openalex.org/W2798913983","https://openalex.org/W2883888092","https://openalex.org/W2884115684","https://openalex.org/W2887842788","https://openalex.org/W2889631368","https://openalex.org/W2889960480","https://openalex.org/W2891951760","https://openalex.org/W2895643041","https://openalex.org/W2901026139","https://openalex.org/W2903811598","https://openalex.org/W2908035133","https://openalex.org/W2943605315","https://openalex.org/W2943860728","https://openalex.org/W2948398419","https://openalex.org/W2948606739","https://openalex.org/W2948657385","https://openalex.org/W2951464224","https://openalex.org/W2955425717","https://openalex.org/W2961018736","https://openalex.org/W2962761264","https://openalex.org/W2962762068","https://openalex.org/W2962798326","https://openalex.org/W2962837320","https://openalex.org/W2962887033","https://openalex.org/W2963090248","https://openalex.org/W2963096987","https://openalex.org/W2963113370","https://openalex.org/W2963323244","https://openalex.org/W2963341924","https://openalex.org/W2963351448","https://openalex.org/W2963420272","https://openalex.org/W2963420686","https://openalex.org/W2963516811","https://openalex.org/W2963983207","https://openalex.org/W2964015378","https://openalex.org/W2964105864","https://openalex.org/W2964176323","https://openalex.org/W2964274690","https://openalex.org/W2964292098","https://openalex.org/W2967052791","https://openalex.org/W2969985801","https://openalex.org/W2989980422","https://openalex.org/W2990019157","https://openalex.org/W2996844762","https://openalex.org/W2999659281","https://openalex.org/W3005680577","https://openalex.org/W3016785712","https://openalex.org/W3034617450","https://openalex.org/W3034624317","https://openalex.org/W3034978746","https://openalex.org/W3035060554","https://openalex.org/W3035118106","https://openalex.org/W3035271324","https://openalex.org/W3035524453","https://openalex.org/W3046890131","https://openalex.org/W3104752576","https://openalex.org/W3106250896","https://openalex.org/W3156744082","https://openalex.org/W3176166976","https://openalex.org/W3181598125","https://openalex.org/W4210438927","https://openalex.org/W4300379313","https://openalex.org/W6602324145","https://openalex.org/W6620707391","https://openalex.org/W6638319203","https://openalex.org/W6679390333","https://openalex.org/W6679792166","https://openalex.org/W6693735323","https://openalex.org/W6696078910","https://openalex.org/W6700872662","https://openalex.org/W6701655646","https://openalex.org/W6712938780","https://openalex.org/W6717697761","https://openalex.org/W6725948286","https://openalex.org/W6726873649","https://openalex.org/W6730323794","https://openalex.org/W6736318150","https://openalex.org/W6740005241","https://openalex.org/W6743428213","https://openalex.org/W6743885473","https://openalex.org/W6753069017","https://openalex.org/W6754029020","https://openalex.org/W6754407135","https://openalex.org/W6754854709","https://openalex.org/W6755590075","https://openalex.org/W6756131066","https://openalex.org/W6762718338","https://openalex.org/W6774314701","https://openalex.org/W6779326418","https://openalex.org/W6782958996","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W1571141552","https://openalex.org/W3000197790","https://openalex.org/W3132346564","https://openalex.org/W2991483587","https://openalex.org/W2786391746","https://openalex.org/W2914559142","https://openalex.org/W4226059458","https://openalex.org/W4381430104","https://openalex.org/W2995102745","https://openalex.org/W4225292444"],"abstract_inverted_index":{"Deep":[0],"learning":[1,76,86],"(DL)":[2],"is":[3,17,58],"inherently":[4],"subject":[5],"to":[6,21,26,40,53,125,146,159,175,224],"the":[7,28,42,62,81,95,115,134,161,164,183,218,226,231,234],"requirement":[8],"of":[9,13,30,44,61,83,99,233],"a":[10,55,72,91,127,176,199],"large":[11],"amount":[12],"well-labeled":[14,235],"data,":[15],"which":[16,79],"expensive":[18],"and":[19,110,123,140,153,196],"time-consuming":[20],"obtain":[22],"manually.":[23],"In":[24],"order":[25],"broaden":[27],"reach":[29],"DL,":[31],"leveraging":[32],"free":[33],"web":[34,51,88,108,116],"data":[35,45,52,89,202],"becomes":[36],"an":[37],"attractive":[38],"strategy":[39],"alleviate":[41],"issue":[43],"scarcity.":[46],"However,":[47],"directly":[48],"utilizing":[49],"collected":[50],"train":[54,147],"deep":[56,148,172],"model":[57],"ineffective":[59],"because":[60,189],"mixed":[63],"noisy":[64],"data.":[65],"To":[66],"address":[67],"such":[68,170],"problems,":[69],"we":[70],"develop":[71],"novel":[73],"bidirectional":[74],"self-paced":[75],"(BiSPL)":[77],"framework":[78,97],"reduces":[80],"effect":[82],"noise":[84,162],"by":[85],"from":[87],"in":[90],"meaningful":[92],"order.":[93],"Technically,":[94],"BiSPL":[96,222],"consists":[98],"two":[100],"essential":[101],"steps.":[102],"Relying":[103],"on":[104,133,182,207],"distances":[105,120],"defined":[106],"between":[107],"samples":[109,117,142,155],"labeled":[111],"source":[112],"samples,":[113],"first,":[114],"with":[118],"short":[119],"are":[121,143,156,193],"sampled":[122],"combined":[124],"form":[126],"new":[128,135],"training":[129,136,165,236],"set.":[130],"Second,":[131],"based":[132],"set,":[137],"both":[138],"easy":[139],"hard":[141,154],"initially":[144],"employed":[145],"models":[149,173],"for":[150],"higher":[151],"stability,":[152],"gradually":[157],"dropped":[158],"reduce":[160],"as":[163],"progresses.":[166],"By":[167],"iteratively":[168],"alternating":[169],"steps,":[171],"converge":[174],"better":[177],"solution.":[178],"We":[179],"mainly":[180],"focus":[181],"fine-grained":[184],"visual":[185],"classification":[186],"(FGVC)":[187],"tasks":[188,211],"their":[190],"corresponding":[191],"datasets":[192],"generally":[194],"small":[195],"therefore":[197],"face":[198],"more":[200],"significant":[201],"scarcity":[203],"problem.":[204],"Experiments":[205],"conducted":[206],"six":[208],"public":[209],"FGVC":[210],"demonstrate":[212],"that":[213],"our":[214],"proposed":[215],"method":[216],"outperforms":[217],"state-of-the-art":[219],"approaches.":[220],"Especially,":[221],"suffices":[223],"achieve":[225],"highest":[227],"stable":[228],"performance":[229],"when":[230],"scale":[232],"set":[237],"decreases":[238],"dramatically.":[239]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}