{"id":"https://openalex.org/W4214501853","doi":"https://doi.org/10.1142/s0218001422560092","title":"Adaptive Hardness Indicator Softmax for Deep Face Recognition","display_name":"Adaptive Hardness Indicator Softmax for Deep Face Recognition","publication_year":2022,"publication_date":"2022-02-26","ids":{"openalex":"https://openalex.org/W4214501853","doi":"https://doi.org/10.1142/s0218001422560092"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001422560092","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001422560092","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","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/A5011705049","display_name":"Mao Cai","orcid":"https://orcid.org/0000-0001-8945-1446"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mao Cai","raw_affiliation_strings":["School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084554132","display_name":"Ning Cheng","orcid":"https://orcid.org/0000-0003-0300-9791"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Cheng","raw_affiliation_strings":["School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023402813","display_name":"Chunzheng Cao","orcid":"https://orcid.org/0000-0003-4237-4468"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunzheng Cao","raw_affiliation_strings":["School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100632859","display_name":"Jianwei Yang","orcid":"https://orcid.org/0000-0002-2022-6002"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwei Yang","raw_affiliation_strings":["School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016612979","display_name":"Yunjie Chen","orcid":"https://orcid.org/0000-0002-3131-2547"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunjie Chen","raw_affiliation_strings":["School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I200845125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5016612979"],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":null,"apc_paid":null,"fwci":0.1015,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.34682492,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"36","issue":"04","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":1.0,"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":1.0,"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":0.998199999332428,"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/softmax-function","display_name":"Softmax function","score":0.9839867353439331},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8815739154815674},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7185384035110474},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6693867444992065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6418504118919373},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6400867700576782},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.532977819442749},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.48263272643089294},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.47910621762275696},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.47086301445961},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.45515936613082886},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.447252094745636},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41204696893692017},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.283286988735199},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.26709479093551636},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1596326231956482}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9839867353439331},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8815739154815674},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7185384035110474},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6693867444992065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6418504118919373},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6400867700576782},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.532977819442749},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.48263272643089294},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.47910621762275696},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.47086301445961},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.45515936613082886},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.447252094745636},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41204696893692017},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.283286988735199},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26709479093551636},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1596326231956482},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001422560092","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001422560092","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7400000095367432}],"awards":[{"id":"https://openalex.org/G3199023588","display_name":null,"funder_award_id":"61976241","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G70979341","display_name":"\u591a\u6a21\u6001\u5a74\u5e7c\u513f\u8111\u6838\u78c1\u5171\u632f\u56fe\u50cf\u6d77\u9a6c\u4f53\u5206\u5272\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61672291","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2096733369","https://openalex.org/W2145287260","https://openalex.org/W2194775991","https://openalex.org/W2296073425","https://openalex.org/W2341528187","https://openalex.org/W2404498690","https://openalex.org/W2520774990","https://openalex.org/W2549858646","https://openalex.org/W2606098075","https://openalex.org/W2663800299","https://openalex.org/W2736633948","https://openalex.org/W2737047298","https://openalex.org/W2784163702","https://openalex.org/W2871667416","https://openalex.org/W2882991827","https://openalex.org/W2949007385","https://openalex.org/W2961224374","https://openalex.org/W2962898354","https://openalex.org/W2963113370","https://openalex.org/W2963350250","https://openalex.org/W2963351448","https://openalex.org/W2963466847","https://openalex.org/W2963516811","https://openalex.org/W2963519453","https://openalex.org/W2963671154","https://openalex.org/W2963814162","https://openalex.org/W2963839617","https://openalex.org/W2963861381","https://openalex.org/W2963896050","https://openalex.org/W2963976704","https://openalex.org/W2969985801","https://openalex.org/W2974328324","https://openalex.org/W2978329087","https://openalex.org/W2984006054","https://openalex.org/W2998469040","https://openalex.org/W3034187833","https://openalex.org/W3035693354","https://openalex.org/W3101998545","https://openalex.org/W3103152812","https://openalex.org/W3119687891"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W3095152779","https://openalex.org/W3119773509","https://openalex.org/W3128220219","https://openalex.org/W2982889384","https://openalex.org/W4226227567","https://openalex.org/W2971218105","https://openalex.org/W4287113729","https://openalex.org/W3173314472","https://openalex.org/W2947728370"],"abstract_inverted_index":{"Due":[0],"to":[1,12,28,87,110,127,154],"their":[2],"simplicity":[3],"and":[4,38,64,147,179,190,194],"efficiency,":[5],"the":[6,20,29,35,43,49,54,57,90,113,129,139,145,157],"margin-based":[7,30],"Softmax":[8,31,46,79],"losses":[9,32,47],"are":[10],"proposed":[11,83],"enhance":[13,156],"feature":[14],"discrimination":[15],"in":[16,84,117],"face":[17,72,169],"recognition.":[18],"Recently,":[19],"strategy":[21],"of":[22,56,93,115,138,159],"hard":[23],"sample":[24,50,101],"mining":[25],"is":[26,62,82,125],"incorporated":[27,126],"for":[33],"focusing":[34],"misclassified":[36],"samples":[37],"achieves":[39],"superior":[40,192],"performance.":[41],"However,":[42],"current":[44],"mining-based":[45],"indicate":[48,112],"difficultness":[51,108],"only":[52],"from":[53],"perspective":[55],"negative":[58,140],"cosine":[59,141],"similarity,":[60],"which":[61,143],"local":[63,148],"not":[65],"robust.":[66],"To":[67],"obtain":[68,186],"more":[69,187],"discriminative":[70,188],"deep":[71],"features,":[73],"a":[74,99,121,133],"novel":[75,134],"adaptive":[76],"hardness":[77,91,102,149],"indicator":[78,103,124,150],"(AHI-Softmax)":[80],"loss":[81],"this":[85],"paper":[86],"fully":[88],"exploit":[89],"information":[92],"samples.":[94,163],"Our":[95],"AHI-Softmax":[96],"firstly":[97],"defines":[98],"global":[100,146],"function":[104],"that":[105,182],"integrates":[106],"three":[107],"factors":[109],"robustly":[111],"level":[114],"\u201chardness\u201d":[116],"numerical":[118],"form.":[119],"Then,":[120],"training":[122],"stage":[123],"avoid":[128],"convergence":[130],"issue.":[131],"Finally,":[132],"sample-related":[135],"modulation":[136],"coefficient":[137],"similarity":[142],"combines":[144],"will":[151],"be":[152],"defined":[153],"further":[155],"differentiation":[158],"constraints":[160],"imposed":[161],"on":[162,167],"The":[164],"experimental":[165],"results":[166],"general":[168],"datasets,":[170],"including":[171],"LFW,":[172],"AgeDB-30,":[173],"CFP-FP,":[174],"CALFW,":[175],"CPLFW,":[176],"MegaFace,":[177],"IJB-B":[178],"IJB-C,":[180],"show":[181],"our":[183],"method":[184],"can":[185],"features":[189],"achieve":[191],"verification":[193],"recognition":[195],"results.":[196]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-06T09:05:17.133730","created_date":"2025-10-10T00:00:00"}