{"id":"https://openalex.org/W4414537267","doi":"https://doi.org/10.1186/s13638-025-02483-8","title":"YAMNet-based transfer learning for compact noise classification in urban and wireless systems","display_name":"YAMNet-based transfer learning for compact noise classification in urban and wireless systems","publication_year":2025,"publication_date":"2025-09-26","ids":{"openalex":"https://openalex.org/W4414537267","doi":"https://doi.org/10.1186/s13638-025-02483-8"},"language":"en","primary_location":{"id":"doi:10.1186/s13638-025-02483-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13638-025-02483-8","pdf_url":"https://jwcn-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13638-025-02483-8","source":{"id":"https://openalex.org/S82675988","display_name":"EURASIP Journal on Wireless Communications and Networking","issn_l":"1687-1472","issn":["1687-1472","1687-1499"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Wireless Communications and Networking","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://jwcn-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13638-025-02483-8","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100720052","display_name":"Lifeng Liu","orcid":"https://orcid.org/0000-0003-2732-7399"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"LiFeng Liu","raw_affiliation_strings":["School of Environmental and Chemical Engineering, ShangHai University, 99 Shangda Road, ShangHai, 200444, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Environmental and Chemical Engineering, ShangHai University, 99 Shangda Road, ShangHai, 200444, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026700748","display_name":"Qinneng Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210093674","display_name":"Zhoukou Normal University","ror":"https://ror.org/00jjkh886","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210093674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"QiNan Xu","raw_affiliation_strings":["ZhouKou Normal University, ZhouKou, 466001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ZhouKou Normal University, ZhouKou, 466001, China","institution_ids":["https://openalex.org/I4210093674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069447701","display_name":"Shaohua Mao","orcid":"https://orcid.org/0000-0002-7448-0030"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ShaoHua Mao","raw_affiliation_strings":["School of Environmental and Chemical Engineering, ShangHai University, 99 Shangda Road, ShangHai, 200444, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Environmental and Chemical Engineering, ShangHai University, 99 Shangda Road, ShangHai, 200444, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081863915","display_name":"Jian-Kang Mu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165204","display_name":"Zhuhai Institute of Advanced Technology","ror":"https://ror.org/05r1mzq61","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761","https://openalex.org/I4210165204"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"JianKang Mu","raw_affiliation_strings":["Zhuhai Comleader Information Science & Technology Co., Ltd, Zhuhai, 519060, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhuhai Comleader Information Science & Technology Co., Ltd, Zhuhai, 519060, China","institution_ids":["https://openalex.org/I4210165204"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101390771","display_name":"Xuxia Zhao","orcid":"https://orcid.org/0000-0002-4144-9336"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"XuXia Zhao","raw_affiliation_strings":["School of Information, China Petroleum University, Beijing, 102200, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information, China Petroleum University, Beijing, 102200, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091299248","display_name":"Weihua Song","orcid":"https://orcid.org/0000-0001-7633-7919"},"institutions":[{"id":"https://openalex.org/I4210165204","display_name":"Zhuhai Institute of Advanced Technology","ror":"https://ror.org/05r1mzq61","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761","https://openalex.org/I4210165204"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"WeiHua Song","raw_affiliation_strings":["Zhuhai Comleader Information Science & Technology Co., Ltd, Zhuhai, 519060, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhuhai Comleader Information Science & Technology Co., Ltd, Zhuhai, 519060, China","institution_ids":["https://openalex.org/I4210165204"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102954059","display_name":"Ping Cheng","orcid":"https://orcid.org/0000-0001-5526-1206"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ping Cheng","raw_affiliation_strings":["School of Environmental and Chemical Engineering, ShangHai University, 99 Shangda Road, ShangHai, 200444, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Environmental and Chemical Engineering, ShangHai University, 99 Shangda Road, ShangHai, 200444, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102954059"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":{"value":1665,"currency":"USD","value_usd":1665},"apc_paid":{"value":1665,"currency":"USD","value_usd":1665},"fwci":1.8683,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.86598326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"2025","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","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/T11309","display_name":"Music and Audio Processing","score":0.9993000030517578,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9934999942779541,"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/noise","display_name":"Noise (video)","score":0.6351000070571899},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6111999750137329},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.6014999747276306},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.5562999844551086},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.45890000462532043},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.42899999022483826},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4287000000476837},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.421099990606308},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.420199990272522},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4189999997615814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8891000151634216},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6351000070571899},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6111999750137329},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.6014999747276306},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.5562999844551086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47269999980926514},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.45890000462532043},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.42899999022483826},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4287000000476837},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.421099990606308},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.420199990272522},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4189999997615814},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3772999942302704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3709999918937683},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.3644999861717224},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.36320000886917114},{"id":"https://openalex.org/C86781634","wikidata":"https://www.wikidata.org/wiki/Q2478325","display_name":"Environmental noise","level":3,"score":0.36059999465942383},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.353300005197525},{"id":"https://openalex.org/C100515483","wikidata":"https://www.wikidata.org/wiki/Q3268235","display_name":"Filter bank","level":3,"score":0.34119999408721924},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.31150001287460327},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C2780909371","wikidata":"https://www.wikidata.org/wiki/Q4801092","display_name":"Artificial noise","level":4,"score":0.30219998955726624},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2791000008583069},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.2777000069618225},{"id":"https://openalex.org/C101765175","wikidata":"https://www.wikidata.org/wiki/Q577764","display_name":"Communications system","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s13638-025-02483-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13638-025-02483-8","pdf_url":"https://jwcn-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13638-025-02483-8","source":{"id":"https://openalex.org/S82675988","display_name":"EURASIP Journal on Wireless Communications and Networking","issn_l":"1687-1472","issn":["1687-1472","1687-1499"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Wireless Communications and Networking","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c38116af2eee45f7a1abe850fc7ba885","is_oa":true,"landing_page_url":"https://doaj.org/article/c38116af2eee45f7a1abe850fc7ba885","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EURASIP Journal on Wireless Communications and Networking, Vol 2025, Iss 1, Pp 1-22 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13638-025-02483-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13638-025-02483-8","pdf_url":"https://jwcn-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13638-025-02483-8","source":{"id":"https://openalex.org/S82675988","display_name":"EURASIP Journal on Wireless Communications and Networking","issn_l":"1687-1472","issn":["1687-1472","1687-1499"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Wireless Communications and Networking","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1006843097","display_name":null,"funder_award_id":"No. 41877374","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1646829957","display_name":null,"funder_award_id":"21SQBS01900","funder_id":"https://openalex.org/F4320313610","funder_display_name":"Shanghai Science and Technology Development Foundation"},{"id":"https://openalex.org/G2190174025","display_name":null,"funder_award_id":"No. 21SQBS01900","funder_id":"https://openalex.org/F4320313610","funder_display_name":"Shanghai Science and Technology Development Foundation"},{"id":"https://openalex.org/G47957547","display_name":null,"funder_award_id":"42277217","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5175125919","display_name":null,"funder_award_id":"No.42277217","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5689996698","display_name":null,"funder_award_id":"41877374","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320313610","display_name":"Shanghai Science and Technology Development Foundation","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414537267.pdf","grobid_xml":"https://content.openalex.org/works/W4414537267.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1650531274","https://openalex.org/W1972567154","https://openalex.org/W1981087263","https://openalex.org/W1995562189","https://openalex.org/W2008415856","https://openalex.org/W2012171341","https://openalex.org/W2017543104","https://openalex.org/W2052666245","https://openalex.org/W2052684427","https://openalex.org/W2082886555","https://openalex.org/W2112796928","https://openalex.org/W2132241724","https://openalex.org/W2194775991","https://openalex.org/W2272847350","https://openalex.org/W2487236559","https://openalex.org/W2487315868","https://openalex.org/W2531605135","https://openalex.org/W2593116425","https://openalex.org/W2676925568","https://openalex.org/W2753821816","https://openalex.org/W2766397045","https://openalex.org/W2768083292","https://openalex.org/W2885195348","https://openalex.org/W2888469011","https://openalex.org/W2889227979","https://openalex.org/W2896295604","https://openalex.org/W3014593905","https://openalex.org/W3092956051","https://openalex.org/W3100031071","https://openalex.org/W3130561436","https://openalex.org/W3196974791","https://openalex.org/W4242607419","https://openalex.org/W4292397060","https://openalex.org/W4297374290","https://openalex.org/W4297963616","https://openalex.org/W4310673728","https://openalex.org/W4311171054","https://openalex.org/W4316663959","https://openalex.org/W4327955618","https://openalex.org/W4383820133","https://openalex.org/W4384831795","https://openalex.org/W4385429141","https://openalex.org/W4399850328"],"related_works":[],"abstract_inverted_index":{"Urban":[0],"development":[1],"and":[2,12,19,43,72,83,89,106,115,148,166,177,223,233,248],"construction":[3],"generate":[4],"significant":[5],"noise,":[6],"which":[7],"must":[8],"be":[9],"accurately":[10],"monitored":[11],"classified":[13],"to":[14,29,153,187,235],"effectively":[15],"mitigate":[16],"its":[17],"impact":[18],"ensure":[20],"regulatory":[21],"compliance.":[22],"However,":[23],"traditional":[24],"noise":[25,56,63,199,246],"recognition":[26],"methods":[27],"tend":[28],"perform":[30],"poorly":[31],"in":[32,96,213,220],"complex,":[33],"dynamic":[34],"environments":[35],"because":[36],"they":[37],"rely":[38],"on":[39,172,183],"large":[40],"labeled":[41,122],"datasets":[42],"have":[44],"limited":[45,137],"adaptability.":[46],"To":[47],"overcome":[48],"these":[49],"challenges,":[50],"this":[51],"study":[52],"proposes":[53],"a":[54,61,79,131,240],"novel":[55,62],"source":[57],"classification":[58,64,117,132,191],"framework":[59,65,160],"YAMNet-Trans,":[60],"that":[66,127],"synergizes":[67],"transfer":[68],"learning":[69],"with":[70,136,207],"acoustic":[71,204],"communication":[73,97,208,250],"signal":[74,98,205],"processing":[75,99,206],"techniques.":[76],"By":[77,227],"fine-tuning":[78],"pre-trained":[80],"YAMNet":[81],"model":[82,179],"integrating":[84],"Mel-frequency":[85],"cepstral":[86],"coefficients":[87],"(MFCC)":[88],"short-time":[90],"Fourier":[91],"transform":[92],"(STFT)\u2014techniques":[93],"widely":[94],"used":[95,182],"for":[100,170,217,243],"tasks":[101],"such":[102],"as":[103],"speech":[104],"enhancement":[105],"channel":[107],"equalization\u2014the":[108],"proposed":[109,159],"method":[110,129],"achieves":[111],"robust":[112],"feature":[113],"extraction":[114],"high":[116,229],"accuracy":[118,133],"while":[119],"using":[120],"minimal":[121],"data.":[123],"Experimental":[124],"results":[125],"show":[126],"the":[128,149,155,158,162,173,178,184],"attains":[130],"of":[134,157],"94.21%":[135],"training":[138],"samples,":[139],"outperforming":[140],"benchmark":[141],"models":[142],"including":[143],"ResNet-50,":[144],"VGG-16,":[145],"AST,":[146],"BEATs,":[147],"baseline":[150],"YAMNet.":[151],"Furthermore,":[152],"validate":[154],"applicability":[156],"within":[161,224],"communications":[163],"field,":[164],"MFCC":[165],"STFT":[167],"were":[168],"applied":[169],"denoising":[171],"RML2016.10a":[174],"modulation":[175],"dataset,":[176],"was":[180],"subsequently":[181],"denoised":[185],"dataset":[186],"obtain":[188],"highly":[189],"accurate":[190],"results.":[192],"This":[193],"work":[194],"not":[195],"only":[196],"advances":[197],"urban":[198],"management":[200,247],"but":[201],"also":[202],"bridges":[203],"technologies,":[209],"showcasing":[210],"potential":[211],"applications":[212],"real-time":[214],"anomaly":[215],"detection":[216],"IoT":[218],"networks":[219],"smart":[221],"cities":[222],"5G":[225],"infrastructure.":[226],"combining":[228],"accuracy,":[230],"computational":[231],"efficiency,":[232],"adaptability":[234],"resource-constrained":[236],"environments,":[237],"YAMNet-Trans":[238],"offers":[239],"versatile":[241],"solution":[242],"both":[244],"environmental":[245],"next-generation":[249],"systems.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":3}],"updated_date":"2026-08-02T14:50:37.381335","created_date":"2025-10-10T00:00:00"}
