{"id":"https://openalex.org/W4395070099","doi":"https://doi.org/10.1109/southeastcon52093.2024.10500208","title":"Enhancing P300 Feature Extraction through Multi-Scale Separable Convolution","display_name":"Enhancing P300 Feature Extraction through Multi-Scale Separable Convolution","publication_year":2024,"publication_date":"2024-03-15","ids":{"openalex":"https://openalex.org/W4395070099","doi":"https://doi.org/10.1109/southeastcon52093.2024.10500208"},"language":"en","primary_location":{"id":"doi:10.1109/southeastcon52093.2024.10500208","doi":"https://doi.org/10.1109/southeastcon52093.2024.10500208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/southeastcon52093.2024.10500208","pdf_url":null,"source":{"id":"https://openalex.org/S4393917016","display_name":"IEEE SoutheastCon","issn_l":"1091-0050","issn":["1091-0050"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"SoutheastCon 2024","raw_type":"proceedings-article"},"volume":null,"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/A5002887525","display_name":"Maohua Liu","orcid":"https://orcid.org/0009-0005-4032-7555","observed_orcids":["https://orcid.org/0009-0005-4032-7555"]},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maohua Liu","raw_affiliation_strings":["School of Electrical and Computer Engineering , College of Engineering, University of Georgia,Athens,USA,30602"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering , College of Engineering, University of Georgia,Athens,USA,30602","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100743410","display_name":"Faraz Ahmad","orcid":"https://orcid.org/0000-0002-0405-9910","observed_orcids":["https://orcid.org/0000-0002-0405-9910"]},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Faraz Ahmad","raw_affiliation_strings":["School of Electrical and Computer Engineering , College of Engineering, University of Georgia,Athens,USA,30602"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering , College of Engineering, University of Georgia,Athens,USA,30602","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100528072","display_name":"Jianwei Hao","orcid":"https://orcid.org/0009-0000-1852-4441","observed_orcids":["https://orcid.org/0009-0000-1852-4441"]},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianwei Hao","raw_affiliation_strings":["School of Computing, College of Engineering, University of Georgia,Athens,USA,30602"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, College of Engineering, University of Georgia,Athens,USA,30602","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Muhammad Mehmood","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Muhammad Mehmood","raw_affiliation_strings":["School of Electrical and Computer Engineering , College of Engineering, University of Georgia,Athens,USA,30602"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering , College of Engineering, University of Georgia,Athens,USA,30602","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073906684","display_name":"Ishfaque Ahmed","orcid":"https://orcid.org/0000-0002-0346-1326","observed_orcids":["https://orcid.org/0000-0002-0346-1326"]},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ishfaque Ahmed","raw_affiliation_strings":["Franklin College of Arts and Sciences, University of Georgia,Department of Physics and Astronomy,Athens,USA,30602"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Franklin College of Arts and Sciences, University of Georgia,Department of Physics and Astronomy,Athens,USA,30602","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036344518","display_name":"Fred R. Beyette","orcid":"https://orcid.org/0000-0001-8704-7810","observed_orcids":["https://orcid.org/0000-0001-8704-7810"]},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fred R. Beyette","raw_affiliation_strings":["School of Electrical and Computer Engineering , College of Engineering, University of Georgia,Athens,USA,30602"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering , College of Engineering, University of Georgia,Athens,USA,30602","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I165733156"],"apc_list":null,"apc_paid":null,"fwci":1.5709,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.79154809,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1420","last_page":"1425"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10667","display_name":"Emotion and Mood Recognition","score":0.0,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/p300-detection","display_name":"P300 detection","score":0.8960000276565552},{"id":"https://openalex.org/keywords/event-related-potentials","display_name":"event-related potentials","score":0.9330000281333923},{"id":"https://openalex.org/keywords/brain-computer-interface","display_name":"brain-computer interface","score":0.9399999976158142},{"id":"https://openalex.org/keywords/separable-convolution","display_name":"separable convolution","score":0.8349999785423279},{"id":"https://openalex.org/keywords/multiscale-convolution","display_name":"multi-scale convolution","score":0.9430000185966492},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"feature extraction","score":0.6439999938011169},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8889999985694885},{"id":"https://openalex.org/keywords/eeg-classification","display_name":"EEG classification","score":0.43700000643730164}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7668570876121521},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.7473093271255493},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6523417830467224},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5756450891494751},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5334807634353638},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.525018036365509},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40695980191230774},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37225961685180664},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25353020429611206},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.14978161454200745},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.13682565093040466},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09591817855834961},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.07596954703330994},{"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/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/southeastcon52093.2024.10500208","doi":"https://doi.org/10.1109/southeastcon52093.2024.10500208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/southeastcon52093.2024.10500208","pdf_url":null,"source":{"id":"https://openalex.org/S4393917016","display_name":"IEEE SoutheastCon","issn_l":"1091-0050","issn":["1091-0050"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"SoutheastCon 2024","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1536620489","https://openalex.org/W2150590430","https://openalex.org/W2238628508","https://openalex.org/W2559463885","https://openalex.org/W2741907166","https://openalex.org/W2751159520","https://openalex.org/W2808255765","https://openalex.org/W3102118598","https://openalex.org/W4211166850","https://openalex.org/W4386763635","https://openalex.org/W4390401429"],"related_works":["https://openalex.org/W4406741032","https://openalex.org/W3102118598","https://openalex.org/W4389724359","https://openalex.org/W3217088449","https://openalex.org/W4392456262","https://openalex.org/W3138098462","https://openalex.org/W4390401429","https://openalex.org/W2980669912","https://openalex.org/W4413442527","https://openalex.org/W3194878131"],"abstract_inverted_index":{"P300,":[0],"one":[1],"kind":[2],"of":[3],"Event-Related":[4],"Potentials":[5],"(ERP),":[6],"plays":[7],"a":[8,18,67,91],"crucial":[9],"role":[10],"in":[11,21,33,134],"Brain-Computer":[12],"Interfaces":[13],"(BCIs).":[14],"P300":[15,34,60,98,135],"detection":[16,35],"is":[17],"key":[19],"step":[20],"P300-based":[22],"BCIs.":[23],"Convolutional":[24],"Neural":[25],"Networks":[26],"(CNNs)":[27],"have":[28,56],"emerged":[29],"as":[30],"popular":[31],"solutions":[32],"due":[36],"to":[37,45],"their":[38],"automatic":[39],"feature":[40,61,99,127],"extraction":[41],"capabilities.":[42],"From":[43],"2010":[44],"2021,":[46],"various":[47],"CNN":[48],"architectures":[49],"with":[50,72],"different":[51,115],"layers":[52],"and":[53,130],"convolutional":[54,110],"methods":[55],"been":[57],"developed":[58],"for":[59,97,108,117],"extraction.":[62,100],"Among":[63],"them,":[64],"SepConv1D,":[65,102],"utilizing":[66],"single":[68],"separable":[69,95],"convolution":[70,96],"layer":[71],"only":[73],"4":[74],"kernels":[75],"(or":[76],"225":[77],"parameters),":[78],"has":[79],"achieved":[80],"state-of-the-art":[81],"performance.":[82],"This":[83],"study":[84],"builds":[85],"upon":[86],"SepConv1D's":[87],"success":[88],"by":[89],"proposing":[90],"novel":[92],"approach:":[93],"multi-scale":[94],"Unlike":[101],"which":[103],"employs":[104],"the":[105],"same":[106],"size":[107],"each":[109,118],"kernel,":[111],"our":[112],"approach":[113],"utilizes":[114],"sizes":[116],"kernel.":[119],"Experimental":[120],"results":[121],"demonstrate":[122],"superior":[123],"performance,":[124],"showing":[125],"improved":[126],"saliency":[128],"maps":[129],"higher":[131],"AUC":[132],"values":[133],"detection.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-10-26T11:51:55.731654","created_date":"2024-04-25T00:00:00"}
