{"id":"https://openalex.org/W2779475425","doi":"https://doi.org/10.1109/access.2017.2784800","title":"A Nuclear Norm Based Matrix Regression Based Projections Method for Feature Extraction","display_name":"A Nuclear Norm Based Matrix Regression Based Projections Method for Feature Extraction","publication_year":2017,"publication_date":"2017-12-18","ids":{"openalex":"https://openalex.org/W2779475425","doi":"https://doi.org/10.1109/access.2017.2784800","mag":"2779475425"},"language":"en","primary_location":{"id":"doi:10.1109/access.2017.2784800","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2784800","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.2017.2784800","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100748706","display_name":"Wankou Yang","orcid":"https://orcid.org/0000-0002-6385-6776"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wankou Yang","raw_affiliation_strings":["Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing, China","School of Automation, Southeast University, Nanjing, China","ORCiD"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100635867","display_name":"Jun Li","orcid":"https://orcid.org/0000-0002-1336-2241"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing, China","School of Automation, Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085132445","display_name":"Hao Zheng","orcid":"https://orcid.org/0000-0003-0829-9660"},"institutions":[{"id":"https://openalex.org/I4210128418","display_name":"Nanjing Xiaozhuang University","ror":"https://ror.org/03fnv7n42","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210128418"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zheng","raw_affiliation_strings":["Key Laboratory of Trusted Cloud Computing and Big Data Analysis, Nanjing Xiaozhuang University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Trusted Cloud Computing and Big Data Analysis, Nanjing Xiaozhuang University, Nanjing, China","institution_ids":["https://openalex.org/I4210128418"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073709711","display_name":"Richard Yi Da Xu","orcid":"https://orcid.org/0000-0003-2080-4762"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Richard Yi Da Xu","raw_affiliation_strings":["School of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100748706"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.2942,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.88476585,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"7445","last_page":"7451"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"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/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"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/T10320","display_name":"Neural Networks and Applications","score":0.9797999858856201,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9659000039100647,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6197926998138428},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6134762763977051},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.5898370146751404},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5658870935440063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5351259708404541},{"id":"https://openalex.org/keywords/matrix-representation","display_name":"Matrix representation","score":0.5247172117233276},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5235585570335388},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45318692922592163},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.4122641682624817},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35660332441329956},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32394522428512573},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.17162734270095825},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1401500403881073}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6197926998138428},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6134762763977051},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.5898370146751404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5658870935440063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5351259708404541},{"id":"https://openalex.org/C103275481","wikidata":"https://www.wikidata.org/wiki/Q6787889","display_name":"Matrix representation","level":3,"score":0.5247172117233276},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5235585570335388},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45318692922592163},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4122641682624817},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35660332441329956},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32394522428512573},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.17162734270095825},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1401500403881073},{"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},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2017.2784800","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2784800","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:2feae377fa794c8299d9dbca7a80cb8b","is_oa":true,"landing_page_url":"https://doaj.org/article/2feae377fa794c8299d9dbca7a80cb8b","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 7445-7451 (2018)","raw_type":"article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/123298","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/123298","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1109/access.2017.2784800","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2784800","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":[],"awards":[{"id":"https://openalex.org/G2470178619","display_name":null,"funder_award_id":"61473086","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5569861647","display_name":null,"funder_award_id":"2242016R20014","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7668926298","display_name":null,"funder_award_id":"2242017K40124","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"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":30,"referenced_works":["https://openalex.org/W189912361","https://openalex.org/W1600550542","https://openalex.org/W1904464160","https://openalex.org/W1974097586","https://openalex.org/W1983772724","https://openalex.org/W1985809919","https://openalex.org/W1990319151","https://openalex.org/W1992738091","https://openalex.org/W1997201895","https://openalex.org/W2001141328","https://openalex.org/W2009596443","https://openalex.org/W2012352340","https://openalex.org/W2033419168","https://openalex.org/W2038165640","https://openalex.org/W2046649434","https://openalex.org/W2053186076","https://openalex.org/W2063715296","https://openalex.org/W2070127246","https://openalex.org/W2088900896","https://openalex.org/W2089322632","https://openalex.org/W2097308346","https://openalex.org/W2117553576","https://openalex.org/W2121647436","https://openalex.org/W2125874614","https://openalex.org/W2129812935","https://openalex.org/W2132467081","https://openalex.org/W2132549764","https://openalex.org/W2143103810","https://openalex.org/W3148981562","https://openalex.org/W4238240379"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2037549926","https://openalex.org/W2345479200","https://openalex.org/W2183306018","https://openalex.org/W2849310602","https://openalex.org/W3006008237","https://openalex.org/W2419146053","https://openalex.org/W4388890789","https://openalex.org/W2985118265","https://openalex.org/W2973596648"],"abstract_inverted_index":{"In":[0,42],"the":[1,6,22,28,40,57,63,101],"traditional":[2],"graph":[3,7,102],"embedding":[4],"framework,":[5],"is":[8,17,105],"usually":[9,35],"built":[10],"by":[11,69],"k-NN":[12],"or":[13],"r-ball.":[14],"Since":[15],"it":[16],"difficult":[18],"to":[19,37,99],"manually":[20],"set":[21],"parameters":[23],"k":[24],"and":[25,81,87],"r":[26],"in":[27],"high-dimensional":[29],"space,":[30],"sparse":[31],"representation-based":[32],"methods":[33],"are":[34],"introduced":[36],"automatically":[38],"build":[39,100],"graphs.":[41],"recent":[43],"years,":[44],"nuclear":[45],"norm-based":[46],"matrix":[47],"regression":[48],"(NMR)":[49],"has":[50],"been":[51],"proposed":[52],"for":[53,78],"face":[54,91],"recognition":[55],"using":[56],"low":[58],"rank":[59],"structural":[60],"information":[61],"(i.e.,":[62],"image":[64],"matrix-based":[65],"error":[66],"model).":[67],"Inspired":[68],"NMR,":[70],"we":[71],"give":[72],"a":[73],"NMR-based":[74],"projections":[75],"(NMRP)":[76],"method":[77],"feature":[79,108],"extraction":[80,109],"recognition.":[82],"The":[83],"experiments":[84],"on":[85],"FERET":[86],"extended":[88],"Yale":[89],"B":[90],"databases":[92],"show":[93],"that":[94],"NMR":[95],"can":[96],"be":[97],"used":[98],"while":[103],"NMRP":[104],"an":[106],"effective":[107],"method.":[110]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":3}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
