{"id":"https://openalex.org/W4281676012","doi":"https://doi.org/10.1109/isit50566.2022.9834613","title":"MetaSSD: Meta-Learned Self-Supervised Detection","display_name":"MetaSSD: Meta-Learned Self-Supervised Detection","publication_year":2022,"publication_date":"2022-06-26","ids":{"openalex":"https://openalex.org/W4281676012","doi":"https://doi.org/10.1109/isit50566.2022.9834613"},"language":"en","primary_location":{"id":"doi:10.1109/isit50566.2022.9834613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834613","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","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/A5042482017","display_name":"Moon Jeong Park","orcid":"https://orcid.org/0000-0003-3280-6714"},"institutions":[{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Moon Jeong Park","raw_affiliation_strings":["POSTECH,Graduate School of Artificial Intelligence"],"affiliations":[{"raw_affiliation_string":"POSTECH,Graduate School of Artificial Intelligence","institution_ids":["https://openalex.org/I4210164862"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000550975","display_name":"Jungseul Ok","orcid":"https://orcid.org/0000-0003-4742-2473"},"institutions":[{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jungseul Ok","raw_affiliation_strings":["POSTECH,Graduate School of Artificial Intelligence"],"affiliations":[{"raw_affiliation_string":"POSTECH,Graduate School of Artificial Intelligence","institution_ids":["https://openalex.org/I4210164862"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012803748","display_name":"Yo\u2013Seb Jeon","orcid":"https://orcid.org/0000-0002-2886-157X"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]},{"id":"https://openalex.org/I2799891827","display_name":"Korea Post","ror":"https://ror.org/00p45d091","country_code":"KR","type":"government","lineage":["https://openalex.org/I2799891827","https://openalex.org/I2801339556","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yo-Seb Jeon","raw_affiliation_strings":["POSTECH,Department of Electrical Engineering"],"affiliations":[{"raw_affiliation_string":"POSTECH,Department of Electrical Engineering","institution_ids":["https://openalex.org/I2799891827","https://openalex.org/I123900574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100357248","display_name":"Dongwoo Kim","orcid":"https://orcid.org/0000-0002-6515-5260"},"institutions":[{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Dongwoo Kim","raw_affiliation_strings":["POSTECH,Graduate School of Artificial Intelligence"],"affiliations":[{"raw_affiliation_string":"POSTECH,Graduate School of Artificial Intelligence","institution_ids":["https://openalex.org/I4210164862"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5042482017"],"corresponding_institution_ids":["https://openalex.org/I4210164862"],"apc_list":null,"apc_paid":null,"fwci":0.1044,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.25601484,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"480","last_page":"485"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9997000098228455,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9997000098228455,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9855999946594238,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9829000234603882,"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/computer-science","display_name":"Computer science","score":0.7763140201568604},{"id":"https://openalex.org/keywords/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.73531174659729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6331072449684143},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5845032334327698},{"id":"https://openalex.org/keywords/symbol","display_name":"Symbol (formal)","score":0.5524635314941406},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5511691570281982},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.5351181030273438},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5228084325790405},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.44338881969451904},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.42532479763031006},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.23444879055023193},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.18915662169456482},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.184798002243042}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7763140201568604},{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.73531174659729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6331072449684143},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5845032334327698},{"id":"https://openalex.org/C134400042","wikidata":"https://www.wikidata.org/wiki/Q2372244","display_name":"Symbol (formal)","level":2,"score":0.5524635314941406},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5511691570281982},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.5351181030273438},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5228084325790405},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.44338881969451904},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.42532479763031006},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.23444879055023193},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.18915662169456482},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.184798002243042},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit50566.2022.9834613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834613","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2045407304","https://openalex.org/W2064675550","https://openalex.org/W2097682410","https://openalex.org/W2604763608","https://openalex.org/W2784187484","https://openalex.org/W2794363191","https://openalex.org/W2804075771","https://openalex.org/W2904944666","https://openalex.org/W2948226226","https://openalex.org/W2962956060","https://openalex.org/W2962993320","https://openalex.org/W2963775850","https://openalex.org/W2964121960","https://openalex.org/W2970898848","https://openalex.org/W2990930610","https://openalex.org/W3008026851","https://openalex.org/W3011730771","https://openalex.org/W3031023929","https://openalex.org/W3081045327","https://openalex.org/W3094341901","https://openalex.org/W3097158613","https://openalex.org/W3126364013","https://openalex.org/W3179012301","https://openalex.org/W4289761856","https://openalex.org/W6717367658","https://openalex.org/W6736057607","https://openalex.org/W6750222692","https://openalex.org/W6753146606"],"related_works":["https://openalex.org/W122912556","https://openalex.org/W1586607209","https://openalex.org/W4312414840","https://openalex.org/W2621411691","https://openalex.org/W2271357838","https://openalex.org/W2556866732","https://openalex.org/W2348322200","https://openalex.org/W2981952041","https://openalex.org/W2328989934","https://openalex.org/W4288358127"],"abstract_inverted_index":{"Deep":[0],"learning-based":[1,145],"symbol":[2,103],"detector":[3,104],"gains":[4],"increasing":[5],"attention":[6],"due":[7],"to":[8,30,52,62,64,78,85,117,136],"the":[9,14,45,71,74,87,114,134,142,166],"simple":[10],"algorithm":[11],"design":[12],"than":[13,81,141],"traditional":[15],"model-based":[16],"algorithms":[17],"such":[18],"as":[19],"Viterbi":[20],"and":[21,69,129,156],"BCJR.":[22,161],"The":[23],"supervised":[24,46],"learning":[25,132],"framework":[26],"is":[27,109],"often":[28],"employed":[29],"train":[31,59],"a":[32,49,65,82,100,118],"model,":[33],"where":[34],"true":[35],"symbols":[36,60,76],"are":[37,40],"necessary.":[38],"There":[39],"two":[41],"major":[42],"limitations":[43],"in":[44,171],"approaches:":[47],"a)":[48,111],"model":[50,88,115,135],"needs":[51,77],"be":[53,79],"retrained":[54],"from":[55],"scratch":[56],"when":[57],"new":[58,66,119],"come":[61],"adapt":[63,116],"channel":[67,120,154],"status,":[68],"b)":[70,130],"length":[72],"of":[73,168],"training":[75],"longer":[80],"certain":[83],"threshold":[84],"make":[86],"generalize":[89],"well":[90],"on":[91,123],"unseen":[92],"symbols.":[93],"To":[94],"overcome":[95],"these":[96],"challenges,":[97],"we":[98],"propose":[99],"meta-learning-based":[101],"self-supervised":[102,131],"named":[105],"MetaSSD.":[106],"Our":[107],"contribution":[108],"two-fold:":[110],"meta-learning":[112],"helps":[113,133],"environment":[121],"based":[122],"experience":[124],"with":[125,152,160],"various":[126],"meta-training":[127],"environments,":[128],"use":[137],"relatively":[138],"less":[139],"supervision":[140],"previously":[143],"suggested":[144],"detectors.":[146],"In":[147],"experiments,":[148],"MetaSSD":[149],"outperforms":[150],"OFDM-MMSE":[151],"noisy":[153],"information":[155],"shows":[157],"comparable":[158],"results":[159],"Further":[162],"ablation":[163],"studies":[164],"show":[165],"necessity":[167],"each":[169],"component":[170],"our":[172],"framework.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}