{"id":"https://openalex.org/W2780938819","doi":"https://doi.org/10.1109/dicta.2017.8227405","title":"An Approach for Sequential Dictionary Learning in Nonuniform Noise","display_name":"An Approach for Sequential Dictionary Learning in Nonuniform Noise","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2780938819","doi":"https://doi.org/10.1109/dicta.2017.8227405","mag":"2780938819"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2017.8227405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2017.8227405","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-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/A5066232342","display_name":"Asif Iqbal","orcid":"https://orcid.org/0000-0002-4657-4451"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Asif Iqbal","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, University of Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084681382","display_name":"Abd\u2010Krim Seghouane","orcid":"https://orcid.org/0000-0003-4619-734X"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Abd-Krim Seghouane","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, University of Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066232342"],"corresponding_institution_ids":["https://openalex.org/I165779595"],"apc_list":null,"apc_paid":null,"fwci":1.4406,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80879491,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9932000041007996,"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/computer-science","display_name":"Computer science","score":0.6972965598106384},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.5790426731109619},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5778843760490417},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.55771404504776},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.5443198084831238},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.5141480565071106},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5087688565254211},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4540083110332489},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4410875141620636},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.42143091559410095}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6972965598106384},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.5790426731109619},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5778843760490417},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.55771404504776},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.5443198084831238},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.5141480565071106},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5087688565254211},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4540083110332489},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4410875141620636},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.42143091559410095},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dicta.2017.8227405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2017.8227405","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1495948108","https://openalex.org/W1551219034","https://openalex.org/W1979766935","https://openalex.org/W2027805700","https://openalex.org/W2038688158","https://openalex.org/W2043478128","https://openalex.org/W2044809283","https://openalex.org/W2061191150","https://openalex.org/W2061615939","https://openalex.org/W2063698478","https://openalex.org/W2082114499","https://openalex.org/W2084716923","https://openalex.org/W2123921160","https://openalex.org/W2127271355","https://openalex.org/W2135046866","https://openalex.org/W2140499889","https://openalex.org/W2142940228","https://openalex.org/W2151693816","https://openalex.org/W2153663612","https://openalex.org/W2160547390","https://openalex.org/W2602065399","https://openalex.org/W2608505488","https://openalex.org/W2754345670","https://openalex.org/W2771297143","https://openalex.org/W3090198113","https://openalex.org/W3105543546","https://openalex.org/W4213099427"],"related_works":["https://openalex.org/W2509955295","https://openalex.org/W2016265625","https://openalex.org/W2111634407","https://openalex.org/W2552089492","https://openalex.org/W2113038107","https://openalex.org/W2982240858","https://openalex.org/W2008821896","https://openalex.org/W2157785665","https://openalex.org/W2048023787","https://openalex.org/W2068941797"],"abstract_inverted_index":{"Dictionary":[0],"learning":[1,55,147],"algorithms":[2,20],"have":[3],"received":[4],"widespread":[5],"acceptance":[6],"when":[7],"it":[8],"comes":[9],"to":[10,50,100],"data":[11,59],"analysis":[12],"and":[13,92,116,128],"signal":[14],"representation":[15],"problems.":[16],"However,":[17],"most":[18,66],"existing":[19,69],"assume":[21],"isotropic":[22],"noise.":[23,64],"This":[24],"is":[25,49,74,106],"a":[26,38,52,75],"restrictive":[27],"assumption":[28],"as":[29],"the":[30,68,71,81,84,89,102,110,123,137,144],"noise":[31,85],"across":[32],"samples":[33],"may":[34],"be":[35],"nonuniform":[36,63],"in":[37,88],"number":[39],"of":[40,46,67,83,143],"real":[41],"world":[42],"application.":[43],"The":[44,96],"aim":[45],"this":[47],"article":[48],"propose":[51],"sequential":[53],"dictionary":[54,93,103,125,146],"algorithm":[56,79,139],"for":[57],"measurement":[58],"vectors":[60],"affected":[61],"by":[62],"As":[65],"algorithms,":[70],"proposed":[72,138],"method":[73],"two":[76],"stages":[77],"iterative":[78],"where":[80],"effect":[82],"nature":[86],"appears":[87],"sparse":[90],"coding":[91],"update":[94,104],"stages.":[95],"cost":[97],"function":[98],"used":[99],"derive":[101],"stage":[105],"developed":[107],"based":[108],"on":[109,122,131],"link":[111],"between":[112],"singular":[113],"value":[114],"decomposition":[115],"rank":[117],"one":[118],"matrix":[119],"approximation.":[120],"Results":[121],"simulated":[124],"recovery":[126],"problem":[127],"an":[129],"application":[130],"face":[132],"recognition":[133],"dataset":[134],"shows":[135],"that":[136],"outperforms":[140],"current":[141],"state":[142],"art":[145],"methods.":[148]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}