{"id":"https://openalex.org/W3159246248","doi":"https://doi.org/10.1109/iscas51556.2021.9401551","title":"Multimodal CNN Fusion Architecture with Multi-Features for Heart Sound Classification","display_name":"Multimodal CNN Fusion Architecture with Multi-Features for Heart Sound Classification","publication_year":2021,"publication_date":"2021-04-27","ids":{"openalex":"https://openalex.org/W3159246248","doi":"https://doi.org/10.1109/iscas51556.2021.9401551","mag":"3159246248"},"language":"en","primary_location":{"id":"doi:10.1109/iscas51556.2021.9401551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas51556.2021.9401551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5077569230","display_name":"Kalpeshkumar Ranipa","orcid":"https://orcid.org/0000-0002-0521-998X"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Kalpeshkumar Ranipa","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033247734","display_name":"Wei\u2010Ping Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wei-Ping Zhu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013967994","display_name":"M.N.S. Swamy","orcid":"https://orcid.org/0000-0002-3989-5476"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"M. N. S. Swamy","raw_affiliation_strings":["Concordia University, Montreal, QC, Canada"],"affiliations":[{"raw_affiliation_string":"Concordia University, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077569230"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":2.1851,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.88433017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9991999864578247,"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/T10860","display_name":"Speech and Audio Processing","score":0.9865000247955322,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8021947145462036},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7181108593940735},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.70892333984375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6319470405578613},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6082548499107361},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5415021181106567},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5053399205207825},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.48967912793159485},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.46772539615631104},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.44831377267837524},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.05435797572135925}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8021947145462036},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7181108593940735},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.70892333984375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6319470405578613},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6082548499107361},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5415021181106567},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5053399205207825},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.48967912793159485},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.46772539615631104},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.44831377267837524},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.05435797572135925},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas51556.2021.9401551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas51556.2021.9401551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.699999988079071,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1518164296","https://openalex.org/W1578856370","https://openalex.org/W1993446563","https://openalex.org/W2052958516","https://openalex.org/W2067063385","https://openalex.org/W2093376526","https://openalex.org/W2125324924","https://openalex.org/W2139107403","https://openalex.org/W2148154194","https://openalex.org/W2263065115","https://openalex.org/W2540718148","https://openalex.org/W2593452559","https://openalex.org/W2593628220","https://openalex.org/W2593628332","https://openalex.org/W2619383789","https://openalex.org/W2622526092","https://openalex.org/W2740616720","https://openalex.org/W2901976219","https://openalex.org/W2959951130","https://openalex.org/W2963838685","https://openalex.org/W3035159033","https://openalex.org/W3082624441","https://openalex.org/W3083439345","https://openalex.org/W6734298547","https://openalex.org/W6734306856","https://openalex.org/W6734423291"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2318112981","https://openalex.org/W4312417841","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3],"novel":[4],"multimodal":[5,44,107],"convolutional":[6],"neural":[7],"network":[8],"(CNN)":[9],"fusion":[10,46],"architecture":[11,47],"is":[12,48,103],"proposed":[13,75],"for":[14,68,87],"heart":[15,41,88],"sound":[16,89],"signal":[17],"classification.":[18,90],"Instead":[19],"of":[20,85,101],"using":[21],"features":[22,29,35,86],"from":[23,38,57],"just":[24],"one":[25],"domain,":[26],"general":[27],"frequency":[28],"as":[30,32],"well":[31],"Mel":[33],"domain":[34],"are":[36,65,93],"extracted":[37,72],"the":[39,53,70,82,106,112],"raw":[40],"sound.":[42],"The":[43,74],"CNN":[45,108],"individually":[49],"trained":[50],"based":[51],"on":[52],"feature":[54,59,63],"maps":[55,64],"resulting":[56],"various":[58],"extraction":[60],"methods.":[61],"These":[62],"then":[66],"merged":[67],"optimizing":[69],"diversified":[71],"features.":[73],"method":[76],"provides":[77],"an":[78,98],"opportunity":[79],"to":[80],"explore":[81],"optimal":[83],"selection":[84],"Extensive":[91],"experimentations":[92],"carried":[94],"out,":[95],"showing":[96],"that":[97],"outstanding":[99],"accuracy":[100],"98.5%":[102],"achieved":[104],"by":[105],"architecture,":[109],"which":[110],"outperforms":[111],"other":[113],"state-of-the-art":[114],"approaches.":[115]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}