{"id":"https://openalex.org/W4297911507","doi":"https://doi.org/10.1109/iccc55456.2022.9880733","title":"LOS Acoustic Signal Recognition Indoor Based on the Dynamic Online Training","display_name":"LOS Acoustic Signal Recognition Indoor Based on the Dynamic Online Training","publication_year":2022,"publication_date":"2022-08-11","ids":{"openalex":"https://openalex.org/W4297911507","doi":"https://doi.org/10.1109/iccc55456.2022.9880733"},"language":"en","primary_location":{"id":"doi:10.1109/iccc55456.2022.9880733","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccc55456.2022.9880733","pdf_url":null,"source":{"id":"https://openalex.org/S4363608039","display_name":"2022 IEEE/CIC International Conference on Communications in China (ICCC)","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/CIC International Conference on Communications in China (ICCC)","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/A5010875828","display_name":"Bingnan Qu","orcid":"https://orcid.org/0000-0002-2534-3443"},"institutions":[{"id":"https://openalex.org/I4210147322","display_name":"Shanghai Institute of Microsystem and Information Technology","ror":"https://ror.org/04nytyj38","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210147322"]},{"id":"https://openalex.org/I4210153300","display_name":"Shanghai Research Center for Wireless Communications","ror":"https://ror.org/04xfd0826","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210153300"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingnan Qu","raw_affiliation_strings":["Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences,Shanghai,China,200050","Key Laboratory of Wireless Sensor Network and Communications, SIMIT, CAS, Shanghai, China","University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences,Shanghai,China,200050","institution_ids":["https://openalex.org/I4210147322"]},{"raw_affiliation_string":"Key Laboratory of Wireless Sensor Network and Communications, SIMIT, CAS, Shanghai, China","institution_ids":["https://openalex.org/I4210147322","https://openalex.org/I4210153300"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100433836","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0001-7584-0184"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["School of Construction Machinery, Chang&#x0027;an University,Xi&#x0027;an,China,710064"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Construction Machinery, Chang&#x0027;an University,Xi&#x0027;an,China,710064","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351716","display_name":"Wei He","orcid":"https://orcid.org/0009-0004-3424-5783"},"institutions":[{"id":"https://openalex.org/I4210147322","display_name":"Shanghai Institute of Microsystem and Information Technology","ror":"https://ror.org/04nytyj38","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210147322"]},{"id":"https://openalex.org/I4210153300","display_name":"Shanghai Research Center for Wireless Communications","ror":"https://ror.org/04xfd0826","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210153300"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei He","raw_affiliation_strings":["Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences,Shanghai,China,200050","Key Laboratory of Wireless Sensor Network and Communications, SIMIT, CAS, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences,Shanghai,China,200050","institution_ids":["https://openalex.org/I4210147322"]},{"raw_affiliation_string":"Key Laboratory of Wireless Sensor Network and Communications, SIMIT, CAS, Shanghai, China","institution_ids":["https://openalex.org/I4210147322","https://openalex.org/I4210153300"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393554","display_name":"Tiantian Zhang","orcid":"https://orcid.org/0000-0002-2283-4888"},"institutions":[{"id":"https://openalex.org/I4210147322","display_name":"Shanghai Institute of Microsystem and Information Technology","ror":"https://ror.org/04nytyj38","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210147322"]},{"id":"https://openalex.org/I4210153300","display_name":"Shanghai Research Center for Wireless Communications","ror":"https://ror.org/04xfd0826","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210153300"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiantian Zhang","raw_affiliation_strings":["Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences,Shanghai,China,200050","Key Laboratory of Wireless Sensor Network and Communications, SIMIT, CAS, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences,Shanghai,China,200050","institution_ids":["https://openalex.org/I4210147322"]},{"raw_affiliation_string":"Key Laboratory of Wireless Sensor Network and Communications, SIMIT, CAS, Shanghai, China","institution_ids":["https://openalex.org/I4210147322","https://openalex.org/I4210153300"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077479086","display_name":"Xiaowei Feng","orcid":"https://orcid.org/0000-0002-8666-9383"},"institutions":[{"id":"https://openalex.org/I4210147322","display_name":"Shanghai Institute of Microsystem and Information Technology","ror":"https://ror.org/04nytyj38","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210147322"]},{"id":"https://openalex.org/I4210153300","display_name":"Shanghai Research Center for Wireless Communications","ror":"https://ror.org/04xfd0826","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210153300"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Feng","raw_affiliation_strings":["Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences,Shanghai,China,200050","Key Laboratory of Wireless Sensor Network and Communications, SIMIT, CAS, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences,Shanghai,China,200050","institution_ids":["https://openalex.org/I4210147322"]},{"raw_affiliation_string":"Key Laboratory of Wireless Sensor Network and Communications, SIMIT, CAS, Shanghai, China","institution_ids":["https://openalex.org/I4210147322","https://openalex.org/I4210153300"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9980000257492065,"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/T11698","display_name":"Underwater Acoustics Research","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7941745519638062},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5354839563369751},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5012862682342529},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49546921253204346},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4895523488521576},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48545461893081665},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4721161127090454},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.47189009189605713},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4463563561439514},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.42088061571121216},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3760527968406677},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3355124294757843}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7941745519638062},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5354839563369751},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5012862682342529},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49546921253204346},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4895523488521576},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48545461893081665},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4721161127090454},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.47189009189605713},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4463563561439514},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42088061571121216},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3760527968406677},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3355124294757843},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccc55456.2022.9880733","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccc55456.2022.9880733","pdf_url":null,"source":{"id":"https://openalex.org/S4363608039","display_name":"2022 IEEE/CIC International Conference on Communications in China (ICCC)","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/CIC International Conference on Communications in China (ICCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5699999928474426}],"awards":[{"id":"https://openalex.org/G6463111683","display_name":null,"funder_award_id":"62003053,2020JQ-389","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":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2021429427","https://openalex.org/W2075707868","https://openalex.org/W2603133612","https://openalex.org/W2883672087","https://openalex.org/W2943307824","https://openalex.org/W2963577574","https://openalex.org/W2989691494","https://openalex.org/W2999138477","https://openalex.org/W3043933517","https://openalex.org/W3127876525","https://openalex.org/W3165055106","https://openalex.org/W4214882650","https://openalex.org/W4220904349","https://openalex.org/W4231225162"],"related_works":["https://openalex.org/W2542536020","https://openalex.org/W2783038087","https://openalex.org/W2501210694","https://openalex.org/W3024650197","https://openalex.org/W4280525836","https://openalex.org/W2891787551","https://openalex.org/W2035143285","https://openalex.org/W115891841","https://openalex.org/W2064889786","https://openalex.org/W2433217581"],"abstract_inverted_index":{"Indoor":[0],"positioning":[1],"technology":[2],"based":[3,54],"on":[4,39,55],"acoustic":[5,81,129,168],"signals":[6,27,160,169],"has":[7],"become":[8],"a":[9,22,47],"potential":[10],"solution":[11],"for":[12,74,115,133,158],"indoor":[13,30],"target":[14],"detection":[15],"and":[16,33,112,137,163],"map":[17],"construction.":[18],"However,":[19],"there":[20],"are":[21,131,144],"large":[23],"number":[24],"of":[25,43,51,78,90,127,140,156,167],"nonline-of-sight(NLOS)":[26],"generated":[28],"by":[29,146],"structures":[31],"occlusion,":[32],"recent":[34],"classification":[35,59],"methods":[36],"usually":[37],"rely":[38],"the":[40,56,76,79,84,91,98,102,109,116,135,147,153,164],"massive":[41],"datasets":[42],"artificial":[44],"labeling.":[45],"Therefore,":[46],"dynamic":[48,64,165],"Parent-Child":[49],"method":[50],"online":[52,110],"training":[53,128,134],"Gaussian":[57],"Bayesian":[58,65],"model":[60],"is":[61,72,94,161],"proposed.":[62],"The":[63,87,149],"prior":[66],"probability":[67],"from":[68,171],"temporal":[69],"state":[70],"information":[71],"used":[73],"predicting":[75],"pseudo-label":[77],"streaming":[80,142],"signal":[82],"in":[83,121],"continuous":[85],"path.":[86],"selection":[88],"strategy":[89],"category":[92],"risk":[93],"designed":[95],"to":[96],"process":[97],"reliable":[99],"pseudo-labels.":[100],"With":[101],"highly":[103],"accurate":[104],"pseudo-labeled":[105],"signals,":[106],"we":[107],"conduct":[108],"learning":[111],"knowledge":[113],"accumulation":[114],"Child-Model.":[117,148],"Through":[118],"two":[119],"experiments":[120],"actual":[122],"scenes,":[123],"only":[124],"30":[125],"sets":[126,139],"samples":[130,143],"utilized":[132],"Parent-Model,":[136],"624,632":[138],"unlabeled":[141],"predicted":[145],"result":[150],"represents":[151],"that":[152],"average":[154],"precision":[155],"recognition":[157,166],"LOS":[159],"99.52%,":[162],"received":[170],"moving":[172],"targets":[173],"can":[174],"be":[175],"achieved.":[176]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
