{"id":"https://openalex.org/W3020429576","doi":"https://doi.org/10.1109/tmm.2020.2990063","title":"A Mutually Attentive Co-Training Framework for Semi-Supervised Recognition","display_name":"A Mutually Attentive Co-Training Framework for Semi-Supervised Recognition","publication_year":2020,"publication_date":"2020-04-23","ids":{"openalex":"https://openalex.org/W3020429576","doi":"https://doi.org/10.1109/tmm.2020.2990063","mag":"3020429576"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2020.2990063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2020.2990063","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-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/A5036335729","display_name":"Shaobo Min","orcid":"https://orcid.org/0000-0002-7700-2149"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaobo Min","raw_affiliation_strings":["National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-7700-2149","affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088031350","display_name":"Xuejin Chen","orcid":"https://orcid.org/0000-0003-0478-7018"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuejin Chen","raw_affiliation_strings":["National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0003-0478-7018","affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078162380","display_name":"Hongtao Xie","orcid":"https://orcid.org/0000-0002-6249-5315"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongtao Xie","raw_affiliation_strings":["National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-6249-5315","affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003217535","display_name":"Zheng-Jun Zha","orcid":"https://orcid.org/0000-0003-2510-8993"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng-Jun Zha","raw_affiliation_strings":["National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0003-2510-8993","affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046305086","display_name":"Yongdong Zhang","orcid":"https://orcid.org/0000-0002-1151-1792"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongdong Zhang","raw_affiliation_strings":["National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-1151-1792","affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":1.5645,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.86640657,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"23","issue":null,"first_page":"899","last_page":"910"},"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":0.9990000128746033,"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":0.9990000128746033,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9980000257492065,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9965000152587891,"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":0.880527138710022},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6449282169342041},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6270925402641296},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6137186884880066},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.5704607963562012},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5453859567642212},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.472102552652359},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4409998059272766},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3601577877998352},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.09682562947273254}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.880527138710022},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6449282169342041},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6270925402641296},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6137186884880066},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.5704607963562012},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5453859567642212},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.472102552652359},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4409998059272766},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3601577877998352},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.09682562947273254},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C155202549","wikidata":"https://www.wikidata.org/wiki/Q178803","display_name":"International trade","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","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/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/tmm.2020.2990063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2020.2990063","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5099999904632568,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G1181567750","display_name":null,"funder_award_id":"WK3490000003","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4530701113","display_name":null,"funder_award_id":"WK2100100030","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5683943641","display_name":null,"funder_award_id":"61632006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6179918720","display_name":null,"funder_award_id":"U1936210","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7532226545","display_name":null,"funder_award_id":"2017209","funder_id":"https://openalex.org/F4320322847","funder_display_name":"Youth Innovation Promotion Association of the Chinese Academy of Sciences"},{"id":"https://openalex.org/G8290336390","display_name":null,"funder_award_id":"61525206","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/F4320322847","display_name":"Youth Innovation Promotion Association of the Chinese Academy of Sciences","ror":"https://ror.org/031141b54"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":82,"referenced_works":["https://openalex.org/W369786348","https://openalex.org/W753847829","https://openalex.org/W1560483044","https://openalex.org/W1572720249","https://openalex.org/W1605615716","https://openalex.org/W1901129140","https://openalex.org/W1968817125","https://openalex.org/W1985767166","https://openalex.org/W2000269560","https://openalex.org/W2024082504","https://openalex.org/W2030476695","https://openalex.org/W2037603696","https://openalex.org/W2051090063","https://openalex.org/W2095536970","https://openalex.org/W2108598243","https://openalex.org/W2121056381","https://openalex.org/W2127147316","https://openalex.org/W2135293965","https://openalex.org/W2140535827","https://openalex.org/W2194775991","https://openalex.org/W2238620239","https://openalex.org/W2252268321","https://openalex.org/W2266059378","https://openalex.org/W2412782625","https://openalex.org/W2464708700","https://openalex.org/W2487852963","https://openalex.org/W2530258459","https://openalex.org/W2530816535","https://openalex.org/W2560023338","https://openalex.org/W2571826879","https://openalex.org/W2573673059","https://openalex.org/W2575226059","https://openalex.org/W2576498342","https://openalex.org/W2576818018","https://openalex.org/W2608045553","https://openalex.org/W2608641923","https://openalex.org/W2613041730","https://openalex.org/W2619296796","https://openalex.org/W2733375200","https://openalex.org/W2737892366","https://openalex.org/W2741891296","https://openalex.org/W2752782242","https://openalex.org/W2752971446","https://openalex.org/W2763160469","https://openalex.org/W2766594578","https://openalex.org/W2788798739","https://openalex.org/W2792945361","https://openalex.org/W2798795235","https://openalex.org/W2805577703","https://openalex.org/W2806321514","https://openalex.org/W2951970475","https://openalex.org/W2952133801","https://openalex.org/W2962762541","https://openalex.org/W2962891704","https://openalex.org/W2963420686","https://openalex.org/W2963488642","https://openalex.org/W2963495494","https://openalex.org/W2963735582","https://openalex.org/W2963785012","https://openalex.org/W2964234160","https://openalex.org/W2964292098","https://openalex.org/W2972825513","https://openalex.org/W2979838725","https://openalex.org/W2984722729","https://openalex.org/W3009323895","https://openalex.org/W3023763517","https://openalex.org/W3100882149","https://openalex.org/W6639824700","https://openalex.org/W6678280073","https://openalex.org/W6680878686","https://openalex.org/W6691441656","https://openalex.org/W6731742386","https://openalex.org/W6731905213","https://openalex.org/W6732103267","https://openalex.org/W6732284500","https://openalex.org/W6732476973","https://openalex.org/W6743885473","https://openalex.org/W6748760166","https://openalex.org/W6751647823","https://openalex.org/W6764051988","https://openalex.org/W6767974129","https://openalex.org/W6770253249"],"related_works":["https://openalex.org/W2006651773","https://openalex.org/W2027050655","https://openalex.org/W3028244590","https://openalex.org/W4254349500","https://openalex.org/W2014369232","https://openalex.org/W3122042562","https://openalex.org/W2050078012","https://openalex.org/W2060761133","https://openalex.org/W2360307734","https://openalex.org/W2028424651"],"abstract_inverted_index":{"Self-training":[0],"plays":[1],"an":[2],"important":[3],"role":[4],"in":[5],"practical":[6],"recognition":[7],"applications":[8],"where":[9],"sufficient":[10],"clean":[11],"labels":[12,22,61,125,142,170,199],"are":[13,82],"unavailable.":[14],"Existing":[15],"methods":[16],"focus":[17],"on":[18,62,182],"generating":[19],"reliable":[20],"pseudo":[21,169],"to":[23,35,111,129,151,154,166,197],"retrain":[24],"a":[25,45,160],"model,":[26],"while":[27],"ignoring":[28],"the":[29,56,78,95,102,120,136,168,173],"importance":[30],"of":[31,59,123],"improving":[32],"model":[33,63,68],"reliability":[34],"those":[36],"inevitably":[37],"mislabeled":[38],"data.":[39],"In":[40,158],"this":[41],"paper,":[42],"we":[43],"propose":[44],"novel":[46],"Mutually":[47],"Attentive":[48],"Co-training":[49],"Framework":[50],"(MACF)":[51],"that":[52,76,192],"can":[53,143],"effectively":[54,145],"alleviate":[55],"negative":[57],"impacts":[58],"incorrect":[60,124,141,156],"retraining":[64],"by":[65,84,118,140,171],"exploring":[66,119],"deep":[67],"disagreements.":[69],"Specifically,":[70],"MACF":[71,193],"trains":[72],"two":[73,99],"symmetrical":[74],"sub-networks":[75,100],"have":[77],"same":[79,103],"input":[80,104],"and":[81,105,177,188],"connected":[83],"several":[85],"attention":[86,92,107,131],"modules":[87],"at":[88,126],"different":[89,127],"layers.":[90],"Each":[91],"module":[93],"analyzes":[94],"inferred":[96],"features":[97],"from":[98,175],"for":[101,109,147],"feedback":[106],"maps":[108],"them":[110],"indicate":[112],"noisy":[113,137,198],"gradients.":[114],"This":[115],"is":[116,164,194],"realized":[117],"back-propagation":[121],"process":[122],"layers":[128],"design":[130],"modules.":[132],"By":[133],"multi-layer":[134],"interception,":[135],"gradients":[138],"caused":[139],"be":[144],"reduced":[146],"both":[148],"sub-networks,":[149],"leading":[150],"robust":[152,196],"training":[153],"potential":[155],"labels.":[157],"addition,":[159],"hierarchical":[161],"distillation":[162],"strategy":[163],"developed":[165],"improve":[167],"aggregating":[172],"predictions":[174],"multi-models":[176],"data":[178],"transformations.":[179],"The":[180],"experiments":[181],"six":[183],"general":[184],"benchmarks,":[185],"including":[186],"classification":[187],"biomedical":[189],"segmentation,":[190],"demonstrate":[191],"much":[195],"than":[200],"previous":[201],"methods.":[202]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}