{"id":"https://openalex.org/W4402352834","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651094","title":"Sample Mining Loss Based on Noise Label and Low-Quality Sample for Face Recognition","display_name":"Sample Mining Loss Based on Noise Label and Low-Quality Sample for Face Recognition","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352834","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651094"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651094","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10651094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100334836","display_name":"Lu Ye","orcid":"https://orcid.org/0000-0001-9601-6645"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Lu","raw_affiliation_strings":["Guangdong University of Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology,China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100689319","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0002-2269-2912"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["Guangdong University of Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology,China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115591883","display_name":"Hailin Liu","orcid":"https://orcid.org/0009-0001-2293-5670"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai-Lin Liu","raw_affiliation_strings":["Guangdong University of Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology,China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998000264167786,"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/T10057","display_name":"Face and Expression Recognition","score":0.9990000128746033,"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/T10828","display_name":"Biometric Identification and Security","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/sample","display_name":"Sample (material)","score":0.7288321852684021},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6338328719139099},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5919867753982544},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5621593594551086},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5413011312484741},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4599522650241852},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.45604023337364197},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4419451355934143},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33338284492492676}],"concepts":[{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.7288321852684021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6338328719139099},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5919867753982544},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5621593594551086},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5413011312484741},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4599522650241852},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.45604023337364197},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4419451355934143},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33338284492492676},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651094","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10651094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W2096733369","https://openalex.org/W2144172034","https://openalex.org/W2194775991","https://openalex.org/W2341528187","https://openalex.org/W2404498690","https://openalex.org/W2515770085","https://openalex.org/W2520774990","https://openalex.org/W2555897561","https://openalex.org/W2609575245","https://openalex.org/W2663800299","https://openalex.org/W2752828042","https://openalex.org/W2784163702","https://openalex.org/W2887500939","https://openalex.org/W2949007385","https://openalex.org/W2962898354","https://openalex.org/W2963351448","https://openalex.org/W2963466847","https://openalex.org/W2963516811","https://openalex.org/W2963519453","https://openalex.org/W2963656735","https://openalex.org/W2963839617","https://openalex.org/W2967637014","https://openalex.org/W2969985801","https://openalex.org/W2970084480","https://openalex.org/W2986295374","https://openalex.org/W2998469040","https://openalex.org/W3035693354","https://openalex.org/W3101227480","https://openalex.org/W3101998545","https://openalex.org/W3103152812","https://openalex.org/W3108537278","https://openalex.org/W3109225549","https://openalex.org/W3169129566","https://openalex.org/W3176307736","https://openalex.org/W4293478066","https://openalex.org/W4312402191","https://openalex.org/W4312430254","https://openalex.org/W6638046521","https://openalex.org/W6681239517","https://openalex.org/W6730323794","https://openalex.org/W6735013348","https://openalex.org/W6744072679","https://openalex.org/W6842019321"],"related_works":["https://openalex.org/W1185300216","https://openalex.org/W2954163146","https://openalex.org/W2899086345","https://openalex.org/W2896057011","https://openalex.org/W4238675884","https://openalex.org/W2589817099","https://openalex.org/W3033465211","https://openalex.org/W1971600963","https://openalex.org/W2098693229","https://openalex.org/W2384651879"],"abstract_inverted_index":{"Face":[0],"recognition":[1,18],"(FR)":[2],"has":[3],"encountered":[4],"great":[5],"difficulties":[6],"due":[7],"to":[8,45,62],"the":[9,16,32,87,121],"label":[10,35,48,95],"noise":[11,36,49,96],"and":[12,37,50,74,97,118],"low-quality":[13,38,51],"samples":[14,52,100],"in":[15],"face":[17],"database.":[19],"Previous":[20],"studies":[21],"addressed":[22],"these":[23,64],"issues":[24],"through":[25,101],"hard":[26],"sample":[27],"mining,":[28],"focusing":[29],"on":[30,106,113],"preventing":[31],"overfitting":[33],"of":[34,124],"samples.":[39],"However,":[40],"existing":[41],"loss":[42,59,89],"functions":[43],"struggle":[44],"handle":[46],"both":[47],"simultaneously.":[53],"This":[54,91],"paper":[55],"proposes":[56],"a":[57,68,82],"novel":[58],"function,":[60],"NLMFace,":[61],"address":[63],"challenges.":[65],"By":[66],"considering":[67],"sample\u2019s":[69],"ground":[70],"truth":[71],"class":[72,78],"center":[73],"its":[75],"nearest":[76],"negative":[77],"center,":[79],"NLMFace":[80],"incorporates":[81],"new":[83],"mining":[84],"framework":[85],"with":[86,111],"margin-based":[88],"function.":[90],"method":[92],"adaptively":[93],"corrects":[94],"identifies":[98],"high-quality":[99],"data":[102],"mining.":[103],"Extensive":[104],"experiments":[105],"CASIA":[107],"WebFace":[108],"datasets,":[109],"along":[110],"evaluations":[112],"benchmarks":[114],"like":[115],"LFW,":[116],"CPLFW,":[117],"CALFW,":[119],"demonstrate":[120],"superior":[122],"performance":[123],"NLMFace.":[125]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
