{"id":"https://openalex.org/W4408860253","doi":"https://doi.org/10.1109/access.2025.3554583","title":"Exploring Beyond Logits: Hierarchical Dynamic Labeling Based on Embeddings for Semi-Supervised Classification","display_name":"Exploring Beyond Logits: Hierarchical Dynamic Labeling Based on Embeddings for Semi-Supervised Classification","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408860253","doi":"https://doi.org/10.1109/access.2025.3554583"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3554583","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3554583","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3554583","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100609077","display_name":"Jiayi Chen","orcid":"https://orcid.org/0000-0002-1016-4661"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiayi Chen","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020661081","display_name":"Yanbiao Ma","orcid":"https://orcid.org/0000-0002-8472-1475"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanbiao Ma","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi’an, China","Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108972454","display_name":"Wei Dai","orcid":"https://orcid.org/0009-0008-2192-2051"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Dai","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101870486","display_name":"Xiaohua Chen","orcid":"https://orcid.org/0000-0003-0405-3153"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohua Chen","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100386657","display_name":"Shuo Li","orcid":"https://orcid.org/0000-0003-2002-3894"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Li","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi’an, China","Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100609077"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.3032,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91314191,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"13","issue":null,"first_page":"54611","last_page":"54621"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.4839000105857849,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.4839000105857849,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.41780000925064087,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7089418172836304},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5470651984214783},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41638386249542236}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7089418172836304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5470651984214783},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41638386249542236}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3554583","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3554583","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:46c8761f519e44ffb51ff2eccaacf11c","is_oa":true,"landing_page_url":"https://doaj.org/article/46c8761f519e44ffb51ff2eccaacf11c","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 54611-54621 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3554583","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3554583","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W2001386853","https://openalex.org/W2194775991","https://openalex.org/W2963691377","https://openalex.org/W2964137095","https://openalex.org/W2980342181","https://openalex.org/W3012396582","https://openalex.org/W3017967922","https://openalex.org/W3034601242","https://openalex.org/W3104121806","https://openalex.org/W3156669901","https://openalex.org/W3202822534","https://openalex.org/W3212464620","https://openalex.org/W4288738569","https://openalex.org/W4292121845","https://openalex.org/W4310493840","https://openalex.org/W4313415184","https://openalex.org/W4315796325","https://openalex.org/W4316369370","https://openalex.org/W4385695913","https://openalex.org/W4385891218","https://openalex.org/W4385933872","https://openalex.org/W4386076395","https://openalex.org/W4386284129","https://openalex.org/W4386811922","https://openalex.org/W4387968604","https://openalex.org/W4389060483","https://openalex.org/W4391537734","https://openalex.org/W4400523584","https://openalex.org/W6677919164","https://openalex.org/W6733814495","https://openalex.org/W6762913911","https://openalex.org/W6764051988","https://openalex.org/W6765939562","https://openalex.org/W6768920361","https://openalex.org/W6770578729","https://openalex.org/W6773005947","https://openalex.org/W6773116539","https://openalex.org/W6787972765","https://openalex.org/W6791353385","https://openalex.org/W6797119129","https://openalex.org/W6802864417","https://openalex.org/W6839041728","https://openalex.org/W6840452500","https://openalex.org/W6848074689","https://openalex.org/W6849385481","https://openalex.org/W6858240479"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"In":[0],"semi-supervised":[1,129,147,180],"learning,":[2],"methods":[3,42],"that":[4,20,69,157],"rely":[5],"on":[6,44,73],"confidence":[7],"learning":[8],"to":[9,80,109,143,172],"generate":[10,81],"pseudo-labels":[11],"have":[12],"been":[13],"widely":[14],"proposed.":[15],"However,":[16],"increasing":[17],"research":[18],"finds":[19],"when":[21],"faced":[22],"with":[23,103,122],"noisy":[24],"and":[25,76,124,137],"biased":[26],"data,":[27],"the":[28,36,57,138,146,155,170,174],"model\u2019s":[29],"representation":[30,158],"network":[31],"is":[32],"more":[33,161],"reliable":[34,162],"than":[35,163],"classification":[37,58],"network.":[38,59],"Additionally,":[39],"label":[40],"generation":[41,178],"based":[43],"model":[45,74,152],"predictions":[46,75],"often":[47],"show":[48],"poor":[49],"adaptability":[50],"across":[51],"different":[52],"datasets,":[53],"necessitating":[54],"customization":[55],"of":[56,176],"Therefore,":[60],"we":[61],"propose":[62],"a":[63,112],"Hierarchical":[64],"Dynamic":[65],"Labeling":[66],"(HDL)":[67],"algorithm":[68],"does":[70],"not":[71],"depend":[72],"utilizes":[77],"image":[78,105],"embeddings":[79,119],"sample":[82],"labels.":[83],"We":[84,117],"also":[85],"introduce":[86],"an":[87],"adaptive":[88],"method":[89],"for":[90],"selecting":[91],"hyperparameters":[92],"in":[93,179],"HDL,":[94,136],"enhancing":[95],"its":[96],"versatility.":[97],"Moreover,":[98],"HDL":[99],"can":[100],"be":[101],"combined":[102],"general":[104],"encoders":[106],"(e.g.,":[107],"CLIP)":[108],"serve":[110],"as":[111],"fundamental":[113],"data":[114],"processing":[115],"module.":[116],"extract":[118],"from":[120],"datasets":[121],"class-balanced":[123],"long-tailed":[125],"distributions":[126],"using":[127,135],"pre-trained":[128],"models.":[130,148],"Subsequently,":[131],"samples":[132,140],"are":[133,141,160],"re-labeled":[134,139],"used":[142],"further":[144],"train":[145],"Experiments":[149],"demonstrate":[150],"improved":[151],"performance,":[153],"validating":[154],"motivation":[156],"networks":[159],"classifiers":[164],"or":[165],"predictors.":[166],"Our":[167],"approach":[168],"has":[169],"potential":[171],"change":[173],"paradigm":[175],"pseudo-label":[177],"learning.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}