{"id":"https://openalex.org/W4390401429","doi":"https://doi.org/10.1109/spmb59478.2023.10372616","title":"BCNN: A Bantamweight Convolutional Neural Network for P300 Detection","display_name":"BCNN: A Bantamweight Convolutional Neural Network for P300 Detection","publication_year":2023,"publication_date":"2023-12-02","ids":{"openalex":"https://openalex.org/W4390401429","doi":"https://doi.org/10.1109/spmb59478.2023.10372616"},"language":"en","primary_location":{"id":"doi:10.1109/spmb59478.2023.10372616","doi":"https://doi.org/10.1109/spmb59478.2023.10372616","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/spmb59478.2023.10372616","pdf_url":null,"source":{"id":"https://openalex.org/S4393918537","display_name":"IEEE Signal Processing in Medicine and Biology Symposium","issn_l":"2372-7241","issn":["2372-7241"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"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":"2023 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","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":null,"display_name":"M. Liu","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":"M. Liu","raw_affiliation_strings":["University of Georgia,School of Electrical and Computer Engineering,Athens,Georgia,USA","School of Electrical and Computer Engineering, University of Georgia, Athens, Georgia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia,School of Electrical and Computer Engineering,Athens,Georgia,USA","institution_ids":["https://openalex.org/I165733156"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Georgia, Athens, Georgia, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100375581","display_name":"Shuang Wang","orcid":"https://orcid.org/0000-0002-5543-6675","observed_orcids":["https://orcid.org/0000-0002-5543-6675","https://orcid.org/0009-0000-0863-2190"]},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"S. Wang","raw_affiliation_strings":["Hebei Normal Univ. of Sci. & Tech,Sch. of Math. and Info. Sci. & Tech,Qinhuangdao,Hebei,China","School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei Normal Univ. of Sci. & Tech,Sch. of Math. and Info. Sci. & Tech,Qinhuangdao,Hebei,China","institution_ids":[]},{"raw_affiliation_string":"School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"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":"F. R. Beyette","raw_affiliation_strings":["University of Georgia,School of Electrical and Computer Engineering,Athens,Georgia,USA","School of Electrical and Computer Engineering, University of Georgia, Athens, Georgia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia,School of Electrical and Computer Engineering,Athens,Georgia,USA","institution_ids":["https://openalex.org/I165733156"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Georgia, Athens, Georgia, USA","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5448,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.82599899,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9994999766349792,"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":0.9994999766349792,"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":9.999999747378752e-05,"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":0.9990000128746033},{"id":"https://openalex.org/keywords/event-related-potentials","display_name":"event-related potentials","score":0.8820000290870667},{"id":"https://openalex.org/keywords/brain-computer-interface","display_name":"brain-computer interface","score":0.8970000147819519},{"id":"https://openalex.org/keywords/p300-speller","display_name":"P300 speller","score":0.871999979019165},{"id":"https://openalex.org/keywords/lightweight-convolutional-neural-network","display_name":"lightweight convolutional neural network","score":0.9449999928474426},{"id":"https://openalex.org/keywords/eeg-classification","display_name":"EEG classification","score":0.47200000286102295},{"id":"https://openalex.org/keywords/resource-constrained-training","display_name":"resource-constrained training","score":0.6480000019073486}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.70918869972229},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6709926128387451},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3709690570831299},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3298454284667969}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/spmb59478.2023.10372616","doi":"https://doi.org/10.1109/spmb59478.2023.10372616","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/spmb59478.2023.10372616","pdf_url":null,"source":{"id":"https://openalex.org/S4393918537","display_name":"IEEE Signal Processing in Medicine and Biology Symposium","issn_l":"2372-7241","issn":["2372-7241"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"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":"2023 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1536620489","https://openalex.org/W2135400163","https://openalex.org/W2222075133","https://openalex.org/W2559463885","https://openalex.org/W2751159520","https://openalex.org/W2807448149","https://openalex.org/W2898211994","https://openalex.org/W2964068654","https://openalex.org/W3102118598","https://openalex.org/W4321497298","https://openalex.org/W6680908784"],"related_works":["https://openalex.org/W3102118598","https://openalex.org/W4413278479","https://openalex.org/W2150590430","https://openalex.org/W4392456262","https://openalex.org/W4406741032","https://openalex.org/W2953853907","https://openalex.org/W3194878131","https://openalex.org/W4386005619","https://openalex.org/W2751159520","https://openalex.org/W3217088449"],"abstract_inverted_index":{"As":[0],"one":[1,110],"kind":[2],"of":[3,75,116,128],"Event-Related":[4],"Potentials":[5],"(ERPs),":[6],"P300":[7,24,55,69,81,105,139],"plays":[8],"an":[9,132],"important":[10],"role":[11],"in":[12,83],"studying":[13],"neural":[14],"activities":[15],"and":[16,19,43,101,113,135,155],"cognitive":[17],"processes,":[18],"lays":[20],"the":[21,27,73,95,99],"foundation":[22],"for":[23,68,80,104,138,147],"speller":[25],"\u2013":[26],"Brain":[28],"Computer":[29],"Interface":[30],"(BCI)":[31],"working":[32],"by":[33,93],"detecting":[34],"P300.":[35],"However,":[36,86],"due":[37],"to":[38,53,72],"P300\u2019s":[39],"high":[40],"subject":[41],"variability":[42],"low":[44],"Signal":[45],"Noise":[46],"Ratio":[47],"(SNR),":[48],"it\u2019s":[49],"always":[50],"a":[51,90,114],"challenge":[52],"do":[54],"detection.":[56,106,140],"Convolutional":[57],"Neural":[58],"Networks":[59],"(CNNs)":[60],"have":[61],"been":[62],"widely":[63],"recognized":[64],"as":[65],"effective":[66],"methods":[67],"detection,":[70],"leading":[71],"development":[74],"increasingly":[76],"complex":[77],"CNN":[78,97,103,137,148],"architectures":[79],"detection":[82],"recent":[84],"years.":[85],"this":[87],"paper":[88],"takes":[89],"different":[91],"approach":[92],"proposing":[94],"bantamweight":[96],"(BCNN),":[98],"simplest":[100],"fast-training":[102],"BCNN":[107,141],"comprises":[108],"only":[109,143],"convolutional":[111],"filter":[112],"total":[115],"141":[117],"parameters.":[118],"Surprisingly,":[119],"it":[120,131],"achieves":[121],"state-of-the-art":[122],"performance":[123],"after":[124],"just":[125],"2":[126],"epochs":[127],"training,":[129],"making":[130],"exceptionally":[133],"lightweight":[134],"fast":[136],"not":[142],"provides":[144],"new":[145],"ideas":[146],"design,":[149],"but":[150],"also":[151],"effectively":[152],"address":[153],"resource":[154],"time":[156],"constrained":[157],"situations.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2023-12-30T00:00:00"}