{"id":"https://openalex.org/W4410325466","doi":"https://doi.org/10.1142/s0218126625503542","title":"Music Genre Classification Using Feature Pyramid Network and Reparameterized Multi-Layer Perceptron with Enhanced Local Prior","display_name":"Music Genre Classification Using Feature Pyramid Network and Reparameterized Multi-Layer Perceptron with Enhanced Local Prior","publication_year":2025,"publication_date":"2025-05-13","ids":{"openalex":"https://openalex.org/W4410325466","doi":"https://doi.org/10.1142/s0218126625503542"},"language":"en","primary_location":{"id":"doi:10.1142/s0218126625503542","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218126625503542","pdf_url":null,"source":{"id":"https://openalex.org/S167602672","display_name":"Journal of Circuits Systems and Computers","issn_l":"0218-1266","issn":["0218-1266","1793-6454"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Circuits, Systems and Computers","raw_type":"journal-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/A5114157615","display_name":"Lei Hua","orcid":null},"institutions":[{"id":"https://openalex.org/I89381930","display_name":"Shangqiu Normal University","ror":"https://ror.org/008m8sh03","country_code":"CN","type":"education","lineage":["https://openalex.org/I89381930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Hua","raw_affiliation_strings":["Conservatory Music, Shangqiu Normal University, Shangqiu, Henan 476000, P. R. China"],"raw_orcid":"https://orcid.org/0009-0005-4132-222X","affiliations":[{"raw_affiliation_string":"Conservatory Music, Shangqiu Normal University, Shangqiu, Henan 476000, P. R. China","institution_ids":["https://openalex.org/I89381930"]}]},{"author_position":"last","author":{"id":null,"display_name":"Haiyang Li","orcid":"https://orcid.org/0009-0000-4241-4824"},"institutions":[{"id":"https://openalex.org/I89381930","display_name":"Shangqiu Normal University","ror":"https://ror.org/008m8sh03","country_code":"CN","type":"education","lineage":["https://openalex.org/I89381930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyang Li","raw_affiliation_strings":["Conservatory Music, Shangqiu Normal University, Shangqiu, Henan 476000, P. R. China"],"raw_orcid":"https://orcid.org/0009-0000-4241-4824","affiliations":[{"raw_affiliation_string":"Conservatory Music, Shangqiu Normal University, Shangqiu, Henan 476000, P. R. China","institution_ids":["https://openalex.org/I89381930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I89381930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10001621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":"01","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9973000288009644,"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/T11309","display_name":"Music and Audio Processing","score":0.9973000288009644,"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/T13996","display_name":"Diverse Musicological Studies","score":0.9244999885559082,"subfield":{"id":"https://openalex.org/subfields/1210","display_name":"Music"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6883769631385803},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.6713519096374512},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6559752225875854},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5880036354064941},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5737266540527344},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5302778482437134},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.508635401725769},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5063349008560181},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4390261769294739},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21483471989631653},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.08570143580436707}],"concepts":[{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6883769631385803},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6713519096374512},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6559752225875854},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5880036354064941},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5737266540527344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5302778482437134},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.508635401725769},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5063349008560181},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4390261769294739},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21483471989631653},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.08570143580436707},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218126625503542","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218126625503542","pdf_url":null,"source":{"id":"https://openalex.org/S167602672","display_name":"Journal of Circuits Systems and Computers","issn_l":"0218-1266","issn":["0218-1266","1793-6454"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Circuits, Systems and Computers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2041084171","https://openalex.org/W2070462330","https://openalex.org/W2133824856","https://openalex.org/W2793881638","https://openalex.org/W2896271387","https://openalex.org/W2935162632","https://openalex.org/W2963499642","https://openalex.org/W2993158215","https://openalex.org/W3017055680","https://openalex.org/W3088047565","https://openalex.org/W3097217077","https://openalex.org/W3107763055","https://openalex.org/W3132747998","https://openalex.org/W3134072853","https://openalex.org/W3154102786","https://openalex.org/W3156038358","https://openalex.org/W3162023064","https://openalex.org/W3179869055","https://openalex.org/W3217269546","https://openalex.org/W3217348973","https://openalex.org/W4206465495","https://openalex.org/W4206716364","https://openalex.org/W4206922450","https://openalex.org/W4220901868","https://openalex.org/W4285109499","https://openalex.org/W4293067765","https://openalex.org/W4312430245","https://openalex.org/W4312573186","https://openalex.org/W4312743288","https://openalex.org/W4312818854","https://openalex.org/W4312906362","https://openalex.org/W4312930446","https://openalex.org/W4313176985","https://openalex.org/W4392904709","https://openalex.org/W4400188211","https://openalex.org/W4401387063","https://openalex.org/W4401641473","https://openalex.org/W4402979463","https://openalex.org/W4404577156"],"related_works":["https://openalex.org/W4206776094","https://openalex.org/W3154920669","https://openalex.org/W3121197456","https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144"],"abstract_inverted_index":{"With":[0],"the":[1,39,51,58,133],"development":[2],"of":[3,42,159],"computer":[4],"technology,":[5],"online":[6],"music-related":[7],"industries":[8],"have":[9],"rapidly":[10],"expanded,":[11],"driving":[12],"demands":[13],"for":[14,96,129],"tasks":[15],"such":[16],"as":[17],"music":[18,25,34,97,113],"genre":[19,26,98],"classification":[20,27,36,143],"and":[21,37,70,123,168],"retrieval.":[22],"Accurate":[23],"computer-based":[24],"is":[28],"a":[29,89,138],"key":[30],"factor":[31],"in":[32,62,78],"enabling":[33],"emotion":[35],"ensuring":[38],"proper":[40],"functioning":[41],"recommendation":[43],"systems.":[44],"Convolutional":[45],"Neural":[46],"Networks":[47],"(CNNs)":[48],"are":[49],"among":[50],"most":[52],"common":[53],"deep":[54],"learning":[55],"models.":[56],"Recently,":[57],"self-attention":[59],"mechanism":[60],"(e.g.,":[61,164],"Transformers)":[63],"has":[64],"gained":[65],"popularity.":[66],"Although":[67],"both":[68],"CNNs":[69],"Transformers":[71],"can":[72],"achieve":[73],"competitive":[74],"performance,":[75],"their":[76],"necessity":[77],"specific":[79],"scenarios":[80],"remains":[81],"debatable.":[82],"To":[83],"address":[84],"this,":[85],"we":[86,101,155],"propose":[87],"FPN-RepMLP,":[88],"Multi-Layer":[90],"Perceptron":[91],"(MLP)":[92],"style":[93],"neural":[94],"network":[95],"classification.":[99],"Specifically,":[100],"enhance":[102],"Fully":[103],"Connected":[104],"(FC)":[105],"layers":[106,122,128],"by":[107,149,171],"incorporating":[108],"local":[109],"priors":[110],"to":[111,146],"strengthen":[112],"category":[114],"recognition.":[115],"During":[116],"training,":[117],"FPN-RepMLP":[118,151],"internally":[119],"constructs":[120],"convolutional":[121],"merges":[124],"them":[125],"into":[126,152],"FC":[127],"inference.":[130],"Experiments":[131],"on":[132],"GTZAN":[134],"dataset":[135],"demonstrate":[136],"that":[137],"simple":[139],"pure":[140],"MLP":[141],"achieves":[142],"accuracy":[144,158],"comparable":[145],"CNNs.":[147],"Furthermore,":[148],"integrating":[150],"traditional":[153],"CNNs,":[154],"attain":[156],"an":[157],"91.36%,":[160],"outperforming":[161],"CNNs-based":[162],"methods":[163],"AlexNet,":[165],"GoogLeNet,":[166],"ResNet)":[167],"Transformer-based":[169],"algorithms":[170],"2.63\u201313.57%":[172],"points.":[173]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}