{"id":"https://openalex.org/W2984035100","doi":"https://doi.org/10.23919/eusipco.2019.8902801","title":"Hyper-Parameter Selection on Convolutional Dictionary Learning Through Local \u2113<sub>0,\u221e</sub> Norm","display_name":"Hyper-Parameter Selection on Convolutional Dictionary Learning Through Local \u2113<sub>0,\u221e</sub> Norm","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2984035100","doi":"https://doi.org/10.23919/eusipco.2019.8902801","mag":"2984035100"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2019.8902801","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8902801","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5032775480","display_name":"Gustavo Silva","orcid":"https://orcid.org/0000-0002-9497-8901"},"institutions":[{"id":"https://openalex.org/I65285256","display_name":"Pontificia Universidad Cat\u00f3lica del Per\u00fa","ror":"https://ror.org/00013q465","country_code":"PE","type":"education","lineage":["https://openalex.org/I65285256"]}],"countries":["PE"],"is_corresponding":false,"raw_author_name":"Gustavo Silva","raw_affiliation_strings":["Electrical Engineering Department, Pontificia Universidad Cat\u00f3lica del Per\u00fa, Lima, Peru"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Pontificia Universidad Cat\u00f3lica del Per\u00fa, Lima, Peru","institution_ids":["https://openalex.org/I65285256"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069617607","display_name":"Jorge R. Quesada","orcid":"https://orcid.org/0000-0002-0438-0691"},"institutions":[{"id":"https://openalex.org/I65285256","display_name":"Pontificia Universidad Cat\u00f3lica del Per\u00fa","ror":"https://ror.org/00013q465","country_code":"PE","type":"education","lineage":["https://openalex.org/I65285256"]}],"countries":["PE"],"is_corresponding":false,"raw_author_name":"Jorge Quesada","raw_affiliation_strings":["Electrical Engineering Department, Pontificia Universidad Cat\u00f3lica del Per\u00fa, Lima, Peru"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Pontificia Universidad Cat\u00f3lica del Per\u00fa, Lima, Peru","institution_ids":["https://openalex.org/I65285256"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077092609","display_name":"Paul Rodr\u00edguez","orcid":"https://orcid.org/0000-0002-8501-0907"},"institutions":[{"id":"https://openalex.org/I65285256","display_name":"Pontificia Universidad Cat\u00f3lica del Per\u00fa","ror":"https://ror.org/00013q465","country_code":"PE","type":"education","lineage":["https://openalex.org/I65285256"]}],"countries":["PE"],"is_corresponding":false,"raw_author_name":"Paul Rodriguez","raw_affiliation_strings":["Electrical Engineering Department, Pontificia Universidad Cat\u00f3lica del Per\u00fa, Lima, Peru"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Pontificia Universidad Cat\u00f3lica del Per\u00fa, Lima, Peru","institution_ids":["https://openalex.org/I65285256"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I65285256"],"apc_list":null,"apc_paid":null,"fwci":0.3196,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.65384203,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.756995439529419},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6461526155471802},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.6063286662101746},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.542803168296814},{"id":"https://openalex.org/keywords/filter-bank","display_name":"Filter bank","score":0.5275138020515442},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.4840054214000702},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4631231725215912},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4534393548965454},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4252658188343048},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41874033212661743},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4131464660167694},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24337157607078552},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1553424596786499}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.756995439529419},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6461526155471802},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.6063286662101746},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.542803168296814},{"id":"https://openalex.org/C100515483","wikidata":"https://www.wikidata.org/wiki/Q3268235","display_name":"Filter bank","level":3,"score":0.5275138020515442},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.4840054214000702},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4631231725215912},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4534393548965454},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4252658188343048},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41874033212661743},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4131464660167694},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24337157607078552},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1553424596786499},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2019.8902801","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8902801","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2008732654","https://openalex.org/W2115429828","https://openalex.org/W2154332973","https://openalex.org/W2164278908","https://openalex.org/W2170942078","https://openalex.org/W2190662802","https://openalex.org/W2362164969","https://openalex.org/W2475058813","https://openalex.org/W2618353736","https://openalex.org/W2790083234","https://openalex.org/W2800754404","https://openalex.org/W2889934972","https://openalex.org/W2891654669","https://openalex.org/W2898781388","https://openalex.org/W2913535645","https://openalex.org/W2936995161","https://openalex.org/W2951400455","https://openalex.org/W2952071070","https://openalex.org/W2963747696","https://openalex.org/W2964140963","https://openalex.org/W4206310440","https://openalex.org/W4244393449","https://openalex.org/W4292363360","https://openalex.org/W6721061755","https://openalex.org/W6741568391","https://openalex.org/W6755943995","https://openalex.org/W6761030284"],"related_works":["https://openalex.org/W2021595906","https://openalex.org/W2766087987","https://openalex.org/W1606020025","https://openalex.org/W106304674","https://openalex.org/W2095992409","https://openalex.org/W2357857030","https://openalex.org/W2035826164","https://openalex.org/W2063491684","https://openalex.org/W2038621399","https://openalex.org/W2085219086"],"abstract_inverted_index":{"Convolutional":[0],"dictionary":[1,51],"learning":[2,116],"(CDL)":[3],"is":[4],"a":[5,38,83,121,133,139,145],"widely":[6],"used":[7],"technique":[8],"in":[9,26,93,148],"many":[10,21],"applications":[11],"on":[12],"the":[13,30,35,42,46,50,56,75,80,87,94,111,125,129,155,159,164],"signal/image":[14],"processing":[15],"and":[16,49,59,96,163],"computer":[17],"vision":[18],"fields.":[19],"While":[20],"algorithms":[22],"have":[23],"been":[24,66],"proposed":[25,141],"order":[27,149],"to":[28,105,150],"improve":[29],"computational":[31],"run-time":[32],"performance":[33,48],"during":[34,79],"training":[36,95],"process,":[37,82],"thorough":[39],"analysis":[40,123],"regarding":[41],"direct":[43],"relationship":[44],"between":[45,154],"reconstruction":[47,165],"features":[52],"(hyper-parameters),":[53],"such":[54],"as":[55,144],"filter":[57,60,161],"size":[58],"bank's":[61],"cardinality,":[62],"has":[63],"not":[64,72],"yet":[65],"presented.As":[67],"arbitrarily":[68],"configured":[69],"dictionaries":[70],"do":[71],"necessarily":[73],"guarantee":[74],"best":[76],"possible":[77,152],"results":[78],"test":[81,168],"correct":[84],"selection":[85],"of":[86,113,124,127],"hyper-parameters":[88,114,131],"would":[89],"be":[90],"very":[91],"favorable":[92],"testing":[97],"stages.":[98],"In":[99],"this":[100,102],"context,":[101],"works":[103],"aims":[104],"provide":[106],"an":[107],"empirical":[108],"support":[109],"for":[110],"choice":[112],"when":[115],"convolutional":[117],"dictionaries.":[118],"We":[119],"perform":[120],"careful":[122],"effect":[126],"varying":[128],"dictionary's":[130],"through":[132],"denoising":[134],"task.":[135],"Furthermore,":[136],"we":[137],"employ":[138],"recently":[140],"local":[142],"\u21130,\u221enorm":[143],"sparsity":[146,156],"measure":[147],"explore":[151],"correlations":[153],"induced":[157],"by":[158],"learned":[160],"bank":[162],"quality":[166],"at":[167],"stage.":[169]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}