{"id":"https://openalex.org/W4385482950","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191701","title":"Cortex Inspired Learning to Recover Damaged Signal Modality with ReD-SOM Model","display_name":"Cortex Inspired Learning to Recover Damaged Signal Modality with ReD-SOM Model","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385482950","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191701"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191701","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","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/A5019289590","display_name":"Artem R. Muliukov","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095736","display_name":"Laboratoire d'\u00c9lectronique, Antennes et T\u00e9l\u00e9communications","ror":"https://ror.org/00ah32k04","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I201841394","https://openalex.org/I4210095736","https://openalex.org/I4210095849"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Artem R. Muliukov","raw_affiliation_strings":["Universit&#x00E9; C&#x00F4;te d&#x0027;Azur,Laboratoire d&#x0027;Electronique, Antennes et T&#x00E9;l&#x00E9;communications (LEAT),Sophia Antipolis,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit&#x00E9; C&#x00F4;te d&#x0027;Azur,Laboratoire d&#x0027;Electronique, Antennes et T&#x00E9;l&#x00E9;communications (LEAT),Sophia Antipolis,France","institution_ids":["https://openalex.org/I4210095736"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079525711","display_name":"Laurent Rodriguez","orcid":"https://orcid.org/0000-0001-9988-5627"},"institutions":[{"id":"https://openalex.org/I4210095736","display_name":"Laboratoire d'\u00c9lectronique, Antennes et T\u00e9l\u00e9communications","ror":"https://ror.org/00ah32k04","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I201841394","https://openalex.org/I4210095736","https://openalex.org/I4210095849"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Laurent Rodriguez","raw_affiliation_strings":["Universit&#x00E9; C&#x00F4;te d&#x0027;Azur,Laboratoire d&#x0027;Electronique, Antennes et T&#x00E9;l&#x00E9;communications (LEAT),Sophia Antipolis,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit&#x00E9; C&#x00F4;te d&#x0027;Azur,Laboratoire d&#x0027;Electronique, Antennes et T&#x00E9;l&#x00E9;communications (LEAT),Sophia Antipolis,France","institution_ids":["https://openalex.org/I4210095736"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080472332","display_name":"Beno\u00eet Miramond","orcid":"https://orcid.org/0000-0002-1229-7046"},"institutions":[{"id":"https://openalex.org/I4210095736","display_name":"Laboratoire d'\u00c9lectronique, Antennes et T\u00e9l\u00e9communications","ror":"https://ror.org/00ah32k04","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I201841394","https://openalex.org/I4210095736","https://openalex.org/I4210095849"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Benoit Miramond","raw_affiliation_strings":["Universit&#x00E9; C&#x00F4;te d&#x0027;Azur,Laboratoire d&#x0027;Electronique, Antennes et T&#x00E9;l&#x00E9;communications (LEAT),Sophia Antipolis,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit&#x00E9; C&#x00F4;te d&#x0027;Azur,Laboratoire d&#x0027;Electronique, Antennes et T&#x00E9;l&#x00E9;communications (LEAT),Sophia Antipolis,France","institution_ids":["https://openalex.org/I4210095736"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019289590"],"corresponding_institution_ids":["https://openalex.org/I4210095736"],"apc_list":null,"apc_paid":null,"fwci":0.3363,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64706018,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"09"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","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/T11447","display_name":"Blind Source Separation Techniques","score":0.9962999820709229,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.828721821308136},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.8043895959854126},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.709924578666687},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.6170969605445862},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6104532480239868},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5962496995925903},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.528731107711792},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5163537263870239},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.50215744972229},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40352576971054077},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.40207040309906006},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32714349031448364},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.11503109335899353},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.11313921213150024}],"concepts":[{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.828721821308136},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.8043895959854126},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.709924578666687},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.6170969605445862},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6104532480239868},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5962496995925903},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.528731107711792},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5163537263870239},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.50215744972229},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40352576971054077},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.40207040309906006},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32714349031448364},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.11503109335899353},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11313921213150024},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191701","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04141988v1","is_oa":false,"landing_page_url":"https://hal.science/hal-04141988","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://ieeexplore.ieee.org/document/10191701","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.47999998927116394,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W65738273","https://openalex.org/W1508613355","https://openalex.org/W1522301498","https://openalex.org/W1901129140","https://openalex.org/W1959608418","https://openalex.org/W1967194987","https://openalex.org/W1969115823","https://openalex.org/W1980511277","https://openalex.org/W1984483979","https://openalex.org/W1990517717","https://openalex.org/W2006493416","https://openalex.org/W2061825952","https://openalex.org/W2064877840","https://openalex.org/W2073165620","https://openalex.org/W2074646893","https://openalex.org/W2084311425","https://openalex.org/W2103104224","https://openalex.org/W2122538988","https://openalex.org/W2194775991","https://openalex.org/W2312101546","https://openalex.org/W2341898073","https://openalex.org/W2750384547","https://openalex.org/W2797583228","https://openalex.org/W2886390999","https://openalex.org/W2894627692","https://openalex.org/W2901917607","https://openalex.org/W2951736998","https://openalex.org/W2995180237","https://openalex.org/W3035414651","https://openalex.org/W3091087057","https://openalex.org/W3091281269","https://openalex.org/W3096831136","https://openalex.org/W3107245349","https://openalex.org/W3136481591","https://openalex.org/W3137758952","https://openalex.org/W3157428506","https://openalex.org/W3189735086","https://openalex.org/W4214871029","https://openalex.org/W4232220759","https://openalex.org/W4234384669","https://openalex.org/W4281823660","https://openalex.org/W4295312788","https://openalex.org/W4393683561","https://openalex.org/W6630323108","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6640963894","https://openalex.org/W6642258339","https://openalex.org/W6755614014","https://openalex.org/W6757925885","https://openalex.org/W6766978945","https://openalex.org/W6838431462"],"related_works":["https://openalex.org/W73545470","https://openalex.org/W4224266612","https://openalex.org/W2383394264","https://openalex.org/W4320153225","https://openalex.org/W4293261942","https://openalex.org/W3125968744","https://openalex.org/W203959209","https://openalex.org/W2167701463","https://openalex.org/W2110287964","https://openalex.org/W4307407935"],"abstract_inverted_index":{"Recent":[0],"progress":[1],"in":[2,51,100,122,125,133,180],"the":[3,36,45,52,55,120,136,144,152,159,168],"fields":[4],"of":[5,23,31,54,63,119,127,131,135,146,165,167,182,186],"AI":[6],"and":[7,14,83,97,177],"cognitive":[8],"sciences":[9],"opens":[10],"up":[11],"new":[12,139],"challenges":[13],"problems":[15],"that":[16],"were":[17],"previously":[18],"inaccessible":[19],"to":[20,78,86,115],"study.":[21],"One":[22],"such":[24,80],"modern":[25],"tasks":[26],"is":[27,173],"recovering":[28],"lost":[29,88],"data":[30,37,89,148],"one":[32,61,134],"modality":[33,62],"by":[34,91,112],"using":[35],"from":[38],"another":[39],"one.":[40],"A":[41],"similar":[42],"effect":[43,82,172],"(called":[44],"McGurk":[46],"Effect)":[47],"has":[48],"been":[49],"found":[50],"functioning":[53],"human":[56],"brain.":[57],"Observing":[58],"this":[59,72],"effect,":[60],"information":[64,132],"interferes":[65],"with":[66],"another,":[67],"changing":[68],"its":[69],"perception.":[70],"In":[71],"paper,":[73],"we":[74],"propose":[75],"a":[76,101,129,183],"way":[77],"reproduce":[79],"an":[81,163],"use":[84,116],"it":[85],"reconstruct":[87],"modalities":[90],"combining":[92],"Variational":[93],"Auto-Encoders,":[94],"Self-Organizing":[95],"Maps,":[96],"Hebb":[98],"connections":[99],"unified":[102],"ReD-SOM":[103],"(Reentering":[104],"Deep":[105],"Self-organizing":[106],"Map)":[107],"model.":[108],"We":[109],"are":[110],"inspired":[111],"human's":[113],"capability":[114],"different":[117,123],"zones":[118],"brain":[121],"modalities,":[124],"case":[126],"having":[128],"lack":[130],"modalities.":[137],"This":[138],"approach":[140],"not":[141],"only":[142],"improves":[143],"analysis":[145],"ambiguous":[147],"but":[149],"also":[150],"restores":[151],"intended":[153],"signal.":[154],"The":[155,171],"results":[156],"obtained":[157],"on":[158],"multimodal":[160],"dataset":[161],"show":[162],"increase":[164],"quality":[166],"signal":[169],"reconstruction.":[170],"remarkable":[174],"both":[175],"visually":[176],"quantitatively,":[178],"specifically":[179],"presence":[181],"significant":[184],"degree":[185],"signal's":[187],"distortion.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2025-10-10T00:00:00"}
