{"id":"https://openalex.org/W4385729931","doi":"https://doi.org/10.1145/3594806.3596566","title":"Learning channel attention for decoding of visual imagined text from multi-band EEG using metric learning","display_name":"Learning channel attention for decoding of visual imagined text from multi-band EEG using metric learning","publication_year":2023,"publication_date":"2023-07-05","ids":{"openalex":"https://openalex.org/W4385729931","doi":"https://doi.org/10.1145/3594806.3596566"},"language":"en","primary_location":{"id":"doi:10.1145/3594806.3596566","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3594806.3596566","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments","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/A5081558484","display_name":"Gaurav Jaswal","orcid":"https://orcid.org/0000-0002-3971-0160"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Gaurav Jaswal","raw_affiliation_strings":["iHub and HCI Foundation Indian Institute of Technology Mandi India, India"],"raw_orcid":"https://orcid.org/0000-0002-3971-0160","affiliations":[{"raw_affiliation_string":"iHub and HCI Foundation Indian Institute of Technology Mandi India, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025377811","display_name":"Geetanjali Sharma","orcid":null},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Geetanjali Sharma","raw_affiliation_strings":["School of Computing and Electrical Engineering, Indian Institute of Technology Mandi India, India"],"raw_orcid":"https://orcid.org/0000-0002-2103-853X","affiliations":[{"raw_affiliation_string":"School of Computing and Electrical Engineering, Indian Institute of Technology Mandi India, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010689942","display_name":"Varun Dutt","orcid":"https://orcid.org/0000-0002-2151-8314"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Varun Dutt","raw_affiliation_strings":["School of Computing and Electrical Engineering, Indian Institute of Technology Mandi India, India"],"raw_orcid":"https://orcid.org/0000-0002-2151-8314","affiliations":[{"raw_affiliation_string":"School of Computing and Electrical Engineering, Indian Institute of Technology Mandi India, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018647189","display_name":"Arnav Bhavsar","orcid":"https://orcid.org/0000-0003-2849-4375"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arnav Bhavsar","raw_affiliation_strings":["School of Computing and Electrical Engineering, Indian Institute of Technology Mandi India, India"],"raw_orcid":"https://orcid.org/0000-0003-2849-4375","affiliations":[{"raw_affiliation_string":"School of Computing and Electrical Engineering, Indian Institute of Technology Mandi India, India","institution_ids":["https://openalex.org/I9579091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5081558484"],"corresponding_institution_ids":["https://openalex.org/I9579091"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10879255,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"720","last_page":"727"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998999834060669,"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":0.9998999834060669,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9976000189781189,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9934999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7724188566207886},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6712496280670166},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6588456630706787},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6546776294708252},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5842399001121521},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5615332126617432},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5221731662750244},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4892856776714325},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4886384606361389},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46564802527427673},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.45370715856552124},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.444087952375412},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.43355727195739746},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.41678112745285034},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.41104692220687866},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4076603651046753},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10486447811126709},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.08750921487808228}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7724188566207886},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6712496280670166},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6588456630706787},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6546776294708252},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5842399001121521},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5615332126617432},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5221731662750244},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4892856776714325},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4886384606361389},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46564802527427673},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.45370715856552124},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.444087952375412},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.43355727195739746},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.41678112745285034},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.41104692220687866},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4076603651046753},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10486447811126709},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.08750921487808228},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","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:10.1145/3594806.3596566","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3594806.3596566","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7200000286102295,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1579279110","https://openalex.org/W2757951733","https://openalex.org/W2897839226","https://openalex.org/W2923625587","https://openalex.org/W2928033176","https://openalex.org/W3101921472","https://openalex.org/W3159850320","https://openalex.org/W4200630155","https://openalex.org/W4206654584","https://openalex.org/W4206798246","https://openalex.org/W4220806194","https://openalex.org/W4220904310","https://openalex.org/W4229378473","https://openalex.org/W4293528129","https://openalex.org/W4309880396","https://openalex.org/W4372343016"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W2387995142","https://openalex.org/W3119773509","https://openalex.org/W3208297503","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611","https://openalex.org/W2619127353"],"abstract_inverted_index":{"The":[0],"electroencephalogram":[1],"(EEG)":[2],"signals":[3],"represent":[4],"proxies":[5],"of":[6,13,24,43,81,127],"the":[7,14,22,25,41,77,93,107,110,125,142,153],"perceptual":[8],"cognitive,":[9],"and":[10,49,84,131,151,183,220],"emotional":[11],"processes":[12],"user,":[15],"which":[16],"allows":[17],"neuro-engineering":[18],"researchers":[19],"to":[20,76,141,168],"decode":[21],"activities":[23],"human":[26],"mind":[27],"non-invasively.":[28],"Many":[29],"studies":[30],"resulting":[31],"in":[32,61,66,92,214],"visual":[33,179,195],"imagined":[34],"brain":[35,68],"decoding":[36,69],"have":[37,57,173],"been":[38,174,190],"proposed":[39],"for":[40,161],"classification":[42],"EEG":[44,181,197,207],"using":[45,148,158],"traditional":[46],"machine":[47],"learning":[48,51,55,105],"deep":[50,54],"algorithms.":[52],"Although":[53],"methods":[56],"achieved":[58,202],"great":[59],"success":[60],"many":[62],"fields,":[63],"their":[64],"performance":[65,139,215],"EEG-based":[67],"analysis":[70],"is":[71,146,156],"still":[72],"limited":[73],"mainly":[74],"due":[75],"relatively":[78],"small":[79],"sizes":[80],"available":[82],"datasets":[83,208],"low":[85,118],"signal-to-noise":[86],"ratio":[87],"characteristics.":[88],"Since":[89],"some":[90],"channels":[91,108],"input":[94],"feature":[95,104,154],"maps":[96],"contain":[97],"more":[98],"prominent":[99],"information,":[100],"we":[101],"capitalize":[102],"discriminative":[103],"across":[106],"through":[109],"channel":[111,120],"attention":[112,121],"mechanism.":[113],"This":[114],"paper":[115],"employs":[116],"a":[117,138,186,193],"parametric":[119],"module":[122],"that":[123],"adopts":[124],"idea":[126],"sparse":[128],"cross-channel":[129],"relationships":[130],"involves":[132],"much":[133],"fewer":[134],"parameters":[135],"but":[136],"brings":[137],"gain":[140],"baseline.":[143],"Prior":[144],"embedding":[145],"obtained":[147],"multi-block":[149],"1DCNN":[150],"then":[152],"vector":[155],"optimized":[157],"triplet":[159],"loss":[160],"inducting":[162],"better":[163],"discriminator":[164],"power.":[165],"In":[166],"order":[167],"show":[169],"network":[170],"generality,":[171],"experiments":[172],"conducted":[175],"on":[176,192,205,216],"an":[177],"In-house":[178],"imagery":[180,196],"dataset":[182],"as":[184,209,211],"well":[185,210],"case":[187],"study":[188],"has":[189,201],"presented":[191],"standard":[194,206],"dataset.":[198],"Our":[199],"framework":[200],"outperforming":[203],"results":[204],"showing":[212],"gains":[213],"in-house":[217],"data":[218],"(Dataset":[219],"code":[221],"will":[222],"be":[223],"made":[224],"publically":[225],"available).":[226]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
