{"id":"https://openalex.org/W4399206165","doi":"https://doi.org/10.1109/access.2024.3407781","title":"Discriminative Regression With Latent Label Learning for Image Classification","display_name":"Discriminative Regression With Latent Label Learning for Image Classification","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399206165","doi":"https://doi.org/10.1109/access.2024.3407781"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3407781","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3407781","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":null,"license_id":null,"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.2024.3407781","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017757620","display_name":"Lang Lang","orcid":"https://orcid.org/0009-0008-8295-4954"},"institutions":[{"id":"https://openalex.org/I50180762","display_name":"Chongqing Three Gorges University","ror":"https://ror.org/05rs3pv16","country_code":"CN","type":"education","lineage":["https://openalex.org/I50180762"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lang Lang","raw_affiliation_strings":["School of Intelligent Manufacturing, Chongqing Three Gorges Vocational College, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Manufacturing, Chongqing Three Gorges Vocational College, Chongqing, China","institution_ids":["https://openalex.org/I50180762"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100594708","display_name":"Xiao Qin Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I50180762","display_name":"Chongqing Three Gorges University","ror":"https://ror.org/05rs3pv16","country_code":"CN","type":"education","lineage":["https://openalex.org/I50180762"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Qin Chen","raw_affiliation_strings":["School of Intelligent Manufacturing, Chongqing Three Gorges Vocational College, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Manufacturing, Chongqing Three Gorges Vocational College, Chongqing, China","institution_ids":["https://openalex.org/I50180762"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069344883","display_name":"Sha Liu","orcid":"https://orcid.org/0000-0003-1434-4333"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sha Liu","raw_affiliation_strings":["National Key Laboratory of Wireless Communications (NKLWC), University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-1434-4333","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Wireless Communications (NKLWC), University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009751003","display_name":"Qiang Zhou","orcid":"https://orcid.org/0000-0002-7902-9732"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Zhou","raw_affiliation_strings":["School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-7902-9732","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12570557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"77675","last_page":"77686"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9972000122070312,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9955000281333923,"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/discriminative-model","display_name":"Discriminative model","score":0.7738024592399597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7082513570785522},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6534759402275085},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6297770142555237},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5073673129081726},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.48713013529777527},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4659012258052826},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.45883554220199585},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3382510542869568},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3103536069393158},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12089422345161438}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7738024592399597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7082513570785522},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6534759402275085},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6297770142555237},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5073673129081726},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.48713013529777527},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4659012258052826},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.45883554220199585},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3382510542869568},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3103536069393158},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12089422345161438}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3407781","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3407781","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ec4b6ce8f0d4409baaffa0eff23aa0cc","is_oa":true,"landing_page_url":"https://doaj.org/article/ec4b6ce8f0d4409baaffa0eff23aa0cc","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 77675-77686 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3407781","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3407781","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W956315800","https://openalex.org/W2003486321","https://openalex.org/W2004427069","https://openalex.org/W2005347517","https://openalex.org/W2014596061","https://openalex.org/W2039468667","https://openalex.org/W2043080228","https://openalex.org/W2065180801","https://openalex.org/W2097486709","https://openalex.org/W2158994553","https://openalex.org/W2174573333","https://openalex.org/W2194775991","https://openalex.org/W2512563520","https://openalex.org/W2531409750","https://openalex.org/W2612496192","https://openalex.org/W2756833625","https://openalex.org/W2763163816","https://openalex.org/W2791052411","https://openalex.org/W2794208501","https://openalex.org/W2860738792","https://openalex.org/W2907110086","https://openalex.org/W2914813387","https://openalex.org/W2969345434","https://openalex.org/W2997239965","https://openalex.org/W3042751648","https://openalex.org/W3094095292","https://openalex.org/W3172444956","https://openalex.org/W3193884581","https://openalex.org/W4206025771","https://openalex.org/W4297775537","https://openalex.org/W4297984473","https://openalex.org/W4321436434","https://openalex.org/W4387309072","https://openalex.org/W4390272507","https://openalex.org/W4391093474","https://openalex.org/W4393931116","https://openalex.org/W6637373629","https://openalex.org/W6737664043"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2761785940","https://openalex.org/W2129933262"],"abstract_inverted_index":{"As":[0],"one":[1],"of":[2,47,102,146,169,177,194],"the":[3,19,39,45,48,52,58,61,87,90,97,103,111,114,119,123,129,134,138,144,148,157,166,170,175,178,191,195,199],"popular":[4],"and":[5,56,155,203],"effective":[6],"supervised":[7],"classification":[8,192],"methods,":[9,89],"linear":[10,30,40],"regression":[11,31,41,76],"is":[12,23,163,185],"extensively":[13],"used":[14],"in":[15,96,122,137],"image":[16,82,209],"classification.":[17,83],"However,":[18],"zero-one":[20,105],"labeling":[21,35,94,106,120],"matrix":[22,131],"too":[24],"strict":[25],"to":[26,29,51,86,132],"be":[27],"conducive":[28],"methods":[32,202,206],"for":[33,81],"learning":[34,205],"information.":[36],"In":[37,84],"addition,":[38],"focuses":[42],"only":[43],"on":[44,207],"fit":[46],"input":[49,104],"features":[50],"corresponding":[53],"output":[54],"labels":[55],"ignores":[57],"distinctiveness":[59],"between":[60,150,159,161],"samples.":[62],"To":[63,127,173],"address":[64],"these":[65],"two":[66],"issues,":[67],"this":[68],"paper":[69],"proposes":[70],"a":[71,140,153],"new":[72],"method,":[73],"namely,":[74],"discriminative":[75,135],"with":[77,143,211],"latent":[78,98],"label":[79,99],"learning,":[80],"contrast":[85],"other":[88],"proposed":[91,115,171,179,196],"method":[92,116,197],"learns":[93],"information":[95,121,136],"space":[100],"instead":[101],"space,":[107],"doing":[108],"so":[109],"has":[110],"advantage":[112],"that":[113,190],"can":[117],"learn":[118,133],"data":[124],"more":[125],"flexibly.":[126],"guide":[128],"transform":[130],"data,":[139],"regularization":[141],"term":[142],"idea":[145],"shortening":[147],"distance":[149,158],"samples":[151,160],"within":[152],"class":[154],"lengthening":[156],"classes":[162],"integrated":[164],"into":[165],"objective":[167],"function":[168],"method.":[172],"obtain":[174],"solution":[176],"model,":[180],"an":[181],"iterative":[182],"optimization":[183],"algorithm":[184],"developed.":[186],"Comprehensive":[187],"experiments":[188],"show":[189],"performance":[193],"outperforms":[198],"current":[200],"state-of-the-art":[201],"deep":[204],"public":[208],"datasets":[210],"small":[212],"sample":[213],"sizes.":[214]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}