{"id":"https://openalex.org/W2911912801","doi":"https://doi.org/10.3390/rs11020193","title":"Nonlocal Tensor Sparse Representation and Low-Rank Regularization for Hyperspectral Image Compressive Sensing Reconstruction","display_name":"Nonlocal Tensor Sparse Representation and Low-Rank Regularization for Hyperspectral Image Compressive Sensing Reconstruction","publication_year":2019,"publication_date":"2019-01-19","ids":{"openalex":"https://openalex.org/W2911912801","doi":"https://doi.org/10.3390/rs11020193","mag":"2911912801"},"language":"en","primary_location":{"id":"doi:10.3390/rs11020193","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11020193","pdf_url":"https://www.mdpi.com/2072-4292/11/2/193/pdf?version=1548156260","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/11/2/193/pdf?version=1548156260","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024046803","display_name":"Jize Xue","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jize Xue","raw_affiliation_strings":["School of Automation, Northwestern Polytechnical University, Xi\u2019an 710072, China","School of Automation, Northwestern Polytechnical University, Xi'an 710072, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Northwestern Polytechnical University, Xi\u2019an 710072, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Automation, Northwestern Polytechnical University, Xi'an 710072, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073503029","display_name":"Yongqiang Zhao","orcid":"https://orcid.org/0000-0002-6974-7327"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongqiang Zhao","raw_affiliation_strings":["Research &amp; Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen 518057, China"],"affiliations":[{"raw_affiliation_string":"Research &amp; Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen 518057, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015582924","display_name":"Wenzhi Liao","orcid":"https://orcid.org/0000-0002-2183-0324"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Wenzhi Liao","raw_affiliation_strings":["Department of Telecommunications and Information Processing, Ghent University-TELIN-IMEC, 9000 Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunications and Information Processing, Ghent University-TELIN-IMEC, 9000 Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047379149","display_name":"Jonathan Cheung-Wai Chan","orcid":"https://orcid.org/0000-0002-3741-1124"},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Jonathan Cheung-Wai Chan","raw_affiliation_strings":["Department of Electronics and Informatics, Vrije, Universiteit Brussel, 1050 Brussel, Belgium"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Informatics, Vrije, Universiteit Brussel, 1050 Brussel, Belgium","institution_ids":["https://openalex.org/I13469542"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073503029"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":8.929,"has_fulltext":true,"cited_by_count":65,"citation_normalized_percentile":{"value":0.99001668,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"11","issue":"2","first_page":"193","last_page":"193"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9993000030517578,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9959999918937683,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8993834257125854},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6048872470855713},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6035323143005371},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5816609859466553},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5621788501739502},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5528419613838196},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.5376573204994202},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5256432294845581},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.49273040890693665},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4190300405025482},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.356947124004364},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32689815759658813},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1527375876903534},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06980514526367188}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8993834257125854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6048872470855713},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6035323143005371},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5816609859466553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5621788501739502},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5528419613838196},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.5376573204994202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5256432294845581},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.49273040890693665},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4190300405025482},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.356947124004364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32689815759658813},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1527375876903534},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06980514526367188},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.3390/rs11020193","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11020193","pdf_url":"https://www.mdpi.com/2072-4292/11/2/193/pdf?version=1548156260","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:vubissmart:VUBISSMART:2000:151620","is_oa":false,"landing_page_url":"https://biblio.vub.ac.be/vubir/nonlocal-tensor-sparse-representation-and-lowrank-regularization-for-hyperspectral-image-compressive-sensing-reconstruction(9e2eff31-b9d9-4aeb-bf67-a51d02052d07).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306402573","display_name":"VUBIR (Vrije Universiteit Brussel)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I13469542","host_organization_name":"Vrije Universiteit Brussel","host_organization_lineage":["https://openalex.org/I13469542"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"publishedVersion"},{"id":"pmh:oai:strathprints.strath.ac.uk:69383","is_oa":false,"landing_page_url":"https://strathprints.strath.ac.uk/view/author/1253631.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4306402226","display_name":"Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I181647926","host_organization_name":"University of Strathclyde","host_organization_lineage":["https://openalex.org/I181647926"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},{"id":"pmh:oai:archive.ugent.be:8604464","is_oa":true,"landing_page_url":"https://biblio.ugent.be/publication/8604464","pdf_url":null,"source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 2072-4292","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:doaj.org/article:1d280a57133040bdad45f92a681f2447","is_oa":true,"landing_page_url":"https://doaj.org/article/1d280a57133040bdad45f92a681f2447","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":"Remote Sensing, Vol 11, Iss 2, p 193 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/11/2/193/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs11020193","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 11; Issue 2; Pages: 193","raw_type":"Text"},{"id":"pmh:oai:vubissmart:VUBISSMART:2000:226761","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402573","display_name":"VUBIR (Vrije Universiteit Brussel)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I13469542","host_organization_name":"Vrije Universiteit Brussel","host_organization_lineage":["https://openalex.org/I13469542"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs11020193","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11020193","pdf_url":"https://www.mdpi.com/2072-4292/11/2/193/pdf?version=1548156260","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8273193886","display_name":null,"funder_award_id":"61371152, 61771391","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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2911912801.pdf","grobid_xml":"https://content.openalex.org/works/W2911912801.grobid-xml"},"referenced_works_count":67,"referenced_works":["https://openalex.org/W652170853","https://openalex.org/W825199928","https://openalex.org/W1481311969","https://openalex.org/W1593447321","https://openalex.org/W1668783296","https://openalex.org/W1799946925","https://openalex.org/W1977355761","https://openalex.org/W1996699294","https://openalex.org/W1998812875","https://openalex.org/W2001380973","https://openalex.org/W2017834485","https://openalex.org/W2018990310","https://openalex.org/W2024165284","https://openalex.org/W2026912518","https://openalex.org/W2045079989","https://openalex.org/W2046658845","https://openalex.org/W2050834445","https://openalex.org/W2071284784","https://openalex.org/W2075394305","https://openalex.org/W2087148018","https://openalex.org/W2091449379","https://openalex.org/W2091494211","https://openalex.org/W2095906131","https://openalex.org/W2107861471","https://openalex.org/W2108188968","https://openalex.org/W2115706991","https://openalex.org/W2130120519","https://openalex.org/W2133665775","https://openalex.org/W2133764833","https://openalex.org/W2135737554","https://openalex.org/W2136251662","https://openalex.org/W2141983208","https://openalex.org/W2158548804","https://openalex.org/W2161011966","https://openalex.org/W2170407643","https://openalex.org/W2170608472","https://openalex.org/W2218665234","https://openalex.org/W2244252827","https://openalex.org/W2326013034","https://openalex.org/W2433081977","https://openalex.org/W2464748116","https://openalex.org/W2505029951","https://openalex.org/W2508114009","https://openalex.org/W2509021534","https://openalex.org/W2517364869","https://openalex.org/W2519420704","https://openalex.org/W2531452236","https://openalex.org/W2573042855","https://openalex.org/W2586224208","https://openalex.org/W2614326984","https://openalex.org/W2630410318","https://openalex.org/W2768095459","https://openalex.org/W2773415061","https://openalex.org/W2789432231","https://openalex.org/W2789471065","https://openalex.org/W2791884754","https://openalex.org/W2793515883","https://openalex.org/W2900379892","https://openalex.org/W3005708632","https://openalex.org/W4250955649","https://openalex.org/W4292363360","https://openalex.org/W6623232459","https://openalex.org/W6677581936","https://openalex.org/W6728784816","https://openalex.org/W6739585996","https://openalex.org/W6749538126","https://openalex.org/W7029332053"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W2969683494","https://openalex.org/W2374021060","https://openalex.org/W2753062694"],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1],"compressive":[2],"sensing":[3],"reconstruction":[4],"(HSI-CSR)":[5],"is":[6],"an":[7,93,137],"important":[8],"issue":[9],"in":[10,36,51,66,136],"remote":[11],"sensing,":[12],"and":[13,38,81,95,117,125],"has":[14,57],"recently":[15],"been":[16,58],"investigated":[17],"increasingly":[18],"by":[19],"the":[20,28,33,62,70,109,131,141,145,156,171],"sparsity":[21,34,91,113],"prior":[22,35],"based":[23,154],"approaches.":[24],"However,":[25],"most":[26,52],"of":[27,69,92,114,144],"available":[29],"HSI-CSR":[30,100,173],"methods":[31],"consider":[32],"spatial":[37,67],"spectral":[39],"vector":[40],"domains":[41],"via":[42],"vectorizing":[43],"hyperspectral":[44],"cubes":[45],"along":[46],"a":[47,77,150],"certain":[48],"dimension.":[49],"Besides,":[50],"previous":[53],"works,":[54],"little":[55],"attention":[56],"paid":[59],"to":[60,106,129],"exploiting":[61],"underlying":[63],"nonlocal":[64,78,132],"structure":[65],"domain":[68],"HSI.":[71,138],"In":[72],"this":[73],"paper,":[74],"we":[75,103,148],"propose":[76],"tensor":[79,116,118,123],"sparse":[80,124],"low-rank":[82,126],"regularization":[83],"(NTSRLR)":[84],"approach,":[85],"which":[86],"can":[87,175],"encode":[88],"essential":[89],"structured":[90],"HSI":[94,167,183],"explore":[96],"its":[97],"advantages":[98],"for":[99,182],"task.":[101],"Specifically,":[102],"study":[104,140],"how":[105],"utilize":[107],"reasonably":[108],"l":[110],"1":[111],"-based":[112],"core":[115],"nuclear":[119],"norm":[120],"function":[121],"as":[122],"regularization,":[127],"respectively,":[128],"describe":[130],"spatial-spectral":[133],"correlation":[134],"hidden":[135],"To":[139],"minimization":[142],"problem":[143],"proposed":[146,172],"algorithm,":[147],"design":[149],"fast":[151],"implementation":[152],"strategy":[153],"on":[155,165],"alternative":[157],"direction":[158],"multiplier":[159],"method":[160],"(ADMM)":[161],"technique.":[162],"Experimental":[163],"results":[164],"various":[166],"datasets":[168],"verify":[169],"that":[170],"algorithm":[174],"significantly":[176],"outperform":[177],"existing":[178],"state-of-the-art":[179],"CSR":[180],"techniques":[181],"recovery.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":20},{"year":2019,"cited_by_count":11}],"updated_date":"2026-04-12T07:58:50.170612","created_date":"2019-02-21T00:00:00"}
