{"id":"https://openalex.org/W2973099107","doi":"https://doi.org/10.1109/tip.2019.2938859","title":"Learning Latent Low-Rank and Sparse Embedding for Robust Image Feature Extraction","display_name":"Learning Latent Low-Rank and Sparse Embedding for Robust Image Feature Extraction","publication_year":2019,"publication_date":"2019-09-10","ids":{"openalex":"https://openalex.org/W2973099107","doi":"https://doi.org/10.1109/tip.2019.2938859","mag":"2973099107","pmid":"https://pubmed.ncbi.nlm.nih.gov/31502975"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2019.2938859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2938859","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5068223297","display_name":"Zhenwen Ren","orcid":"https://orcid.org/0000-0003-3791-9750"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]},{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenwen Ren","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","School of National Defence Science and Technology, Southwest University of Science and Technology, Mianyang, China"],"raw_orcid":"https://orcid.org/0000-0003-3791-9750","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"School of National Defence Science and Technology, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034434932","display_name":"Quansen Sun","orcid":"https://orcid.org/0000-0001-6019-1986"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quansen Sun","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101512415","display_name":"Bin Wu","orcid":"https://orcid.org/0000-0002-8038-1362"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Wu","raw_affiliation_strings":["School of Information Engineering, Southwest University of Science and Technology, Mianyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100408524","display_name":"Xiaoqian Zhang","orcid":"https://orcid.org/0000-0002-4007-4501"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqian Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033299469","display_name":"Wenzhu Yan","orcid":"https://orcid.org/0000-0003-1560-693X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzhu Yan","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5068223297"],"corresponding_institution_ids":["https://openalex.org/I1297991670","https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":9.7101,"has_fulltext":false,"cited_by_count":88,"citation_normalized_percentile":{"value":0.99183592,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"29","issue":"1","first_page":"2094","last_page":"2107"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993000030517578,"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/T12676","display_name":"Machine Learning and ELM","score":0.9965999722480774,"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":0.66893470287323},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6535640954971313},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6453065276145935},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6339488625526428},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6130809187889099},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6086294651031494},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5417599678039551},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5280502438545227},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.49698999524116516},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.49162155389785767},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.44228431582450867}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.66893470287323},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6535640954971313},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6453065276145935},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6339488625526428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6130809187889099},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6086294651031494},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5417599678039551},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5280502438545227},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.49698999524116516},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.49162155389785767},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.44228431582450867},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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":2,"locations":[{"id":"doi:10.1109/tip.2019.2938859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2938859","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:31502975","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31502975","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3830962517","display_name":null,"funder_award_id":"61673220","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":52,"referenced_works":["https://openalex.org/W79405465","https://openalex.org/W384497013","https://openalex.org/W1502638562","https://openalex.org/W1672851775","https://openalex.org/W1897044480","https://openalex.org/W1975900269","https://openalex.org/W1978805590","https://openalex.org/W1997201895","https://openalex.org/W2011994564","https://openalex.org/W2012552975","https://openalex.org/W2027717478","https://openalex.org/W2052730000","https://openalex.org/W2070127246","https://openalex.org/W2083177649","https://openalex.org/W2085400714","https://openalex.org/W2097486709","https://openalex.org/W2097622337","https://openalex.org/W2098461404","https://openalex.org/W2103250033","https://openalex.org/W2103972604","https://openalex.org/W2129812935","https://openalex.org/W2135864704","https://openalex.org/W2136540140","https://openalex.org/W2138424157","https://openalex.org/W2145152441","https://openalex.org/W2145962650","https://openalex.org/W2157400344","https://openalex.org/W2164278908","https://openalex.org/W2189846329","https://openalex.org/W2295652899","https://openalex.org/W2296616510","https://openalex.org/W2327795403","https://openalex.org/W2338953098","https://openalex.org/W2339611261","https://openalex.org/W2516836903","https://openalex.org/W2584047031","https://openalex.org/W2593727049","https://openalex.org/W2608501919","https://openalex.org/W2612496192","https://openalex.org/W2782463043","https://openalex.org/W2791052411","https://openalex.org/W2791459777","https://openalex.org/W2809242293","https://openalex.org/W2883818409","https://openalex.org/W2922411983","https://openalex.org/W4250955649","https://openalex.org/W4292363360","https://openalex.org/W6603183647","https://openalex.org/W6630114213","https://openalex.org/W6637220020","https://openalex.org/W6639690344","https://openalex.org/W6675955514"],"related_works":["https://openalex.org/W2120164251","https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241"],"abstract_inverted_index":{"To":[0,127],"defy":[1],"the":[2,6,12,17,27,33,57,76,89,97,101,111,141,155,159,170,201],"curse":[3],"of":[4,29,59,78,95,100,158,218],"dimensionality,":[5],"inputs":[7],"are":[8],"always":[9],"projected":[10],"from":[11],"original":[13,102,160],"high-dimensional":[14],"space":[15,20],"into":[16,110,200],"target":[18,112],"low-dimension":[19],"for":[21,37,124],"feature":[22,34],"extraction.":[23],"However,":[24],"due":[25],"to":[26,139,153,168,172,190,204],"existence":[28],"noise":[30],"and":[31,177,220],"outliers,":[32],"extraction":[35],"task":[36],"corrupted":[38],"data":[39,85],"is":[40,116,121],"still":[41],"a":[42,46,136,182,196],"challenging":[43],"problem.":[44],"Recently,":[45],"robust":[47],"method":[48,138,209],"called":[49],"low":[50],"rank":[51],"embedding":[52],"(LRE)":[53],"was":[54],"proposed.":[55],"Despite":[56],"success":[58],"LRE":[60,81,106,115],"in":[61,131,216],"experimental":[62],"studies,":[63],"it":[64],"also":[65],"has":[66],"many":[67],"disadvantages:":[68],"1)":[69],"The":[70],"learned":[71],"projection":[72],"cannot":[73],"quantitatively":[74],"interpret":[75],"importance":[77],"features.":[79,144],"2)":[80],"does":[82],"not":[83,92],"perform":[84],"reconstruction":[86],"so":[87],"that":[88],"features":[90,171],"may":[91],"be":[93,173],"capable":[94],"holding":[96],"main":[98,156],"energy":[99,157],"\u201cclean\u201d":[103],"data.":[104,161],"3)":[105],"explicitly":[107],"transforms":[108],"error":[109,188],"space.":[113],"4)":[114],"an":[117,150,165,187],"unsupervised":[118,125],"method,":[119],"which":[120],"only":[122],"suitable":[123],"scenarios.":[126,207],"address":[128],"these":[129],"problems,":[130],"this":[132],"paper,":[133],"we":[134,147,163,180,194],"propose":[135],"novel":[137],"exploit":[140],"latent":[142],"discriminative":[143,176],"In":[145],"particular,":[146],"first":[148],"utilize":[149],"orthogonal":[151],"matrix":[152],"hold":[154],"Next,":[162],"introduce":[164],"12,1-norm":[166,184],"term":[167,199],"encourage":[169],"more":[174],"compact,":[175],"interpretable.":[178],"Then,":[179],"enforce":[181],"columnwise":[183],"constraint":[185],"on":[186,224],"component":[189],"resist":[191],"noise.":[192],"Finally,":[193],"integrate":[195],"classification":[197],"loss":[198],"objective":[202],"function":[203],"fit":[205],"supervised":[206],"Our":[208],"performs":[210],"better":[211],"than":[212],"several":[213],"state-of-the-art":[214],"methods":[215],"terms":[217],"effectiveness":[219],"robustness,":[221],"as":[222],"demonstrated":[223],"six":[225],"publicly":[226],"available":[227],"datasets.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":17}],"updated_date":"2026-05-16T08:24:45.110214","created_date":"2025-10-10T00:00:00"}