{"id":"https://openalex.org/W4415538727","doi":"https://doi.org/10.1145/3746027.3755579","title":"DHGCN: Dual HyperGraph Convolutional Network for EEG-Based Auditory Attention Detection","display_name":"DHGCN: Dual HyperGraph Convolutional Network for EEG-Based Auditory Attention Detection","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415538727","doi":"https://doi.org/10.1145/3746027.3755579"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755579","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","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/A5067137933","display_name":"Jian Zhou","orcid":"https://orcid.org/0000-0001-6509-5520"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Zhou","raw_affiliation_strings":["School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-6509-5520","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yingjie Xie","orcid":"https://orcid.org/0009-0007-5001-4020"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingjie Xie","raw_affiliation_strings":["School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0007-5001-4020","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037493212","display_name":"Cunhang Fan","orcid":"https://orcid.org/0000-0001-6318-8803"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cunhang Fan","raw_affiliation_strings":["School of Computer Science and Technology, State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-6318-8803","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I16365422","https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066775159","display_name":"Huabin Wang","orcid":"https://orcid.org/0000-0001-5938-5409"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huabin Wang","raw_affiliation_strings":["School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-5938-5409","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026466982","display_name":"Zhao Lv","orcid":"https://orcid.org/0000-0003-4530-4422"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Lv","raw_affiliation_strings":["School of Computer Science and Technology, State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0003-4530-4422","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I16365422","https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101917317","display_name":"Liang Tao","orcid":"https://orcid.org/0000-0003-2834-5548"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Tao","raw_affiliation_strings":["School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0003-2834-5548","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5067137933"],"corresponding_institution_ids":["https://openalex.org/I143868143"],"apc_list":null,"apc_paid":null,"fwci":5.0489,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.95701387,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"612","last_page":"620"},"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/T10581","display_name":"Neural dynamics and brain function","score":0.9936000108718872,"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":0.9932000041007996,"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/hypergraph","display_name":"Hypergraph","score":0.8458999991416931},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5968999862670898},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5680999755859375},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.527899980545044},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5109000205993652},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5001999735832214},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.49639999866485596},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.42410001158714294}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.8458999991416931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7111999988555908},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5968999862670898},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5680999755859375},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.527899980545044},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5001999735832214},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.49639999866485596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4945000112056732},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.42410001158714294},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.374099999666214},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3343999981880188},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2761000096797943},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755579","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1947251450","https://openalex.org/W2138164020","https://openalex.org/W2152119085","https://openalex.org/W2310580211","https://openalex.org/W2558748708","https://openalex.org/W2606067354","https://openalex.org/W2771075519","https://openalex.org/W2891871540","https://openalex.org/W2907492528","https://openalex.org/W2966720510","https://openalex.org/W3085990079","https://openalex.org/W3126966983","https://openalex.org/W3159696612","https://openalex.org/W4205620265","https://openalex.org/W4206654584","https://openalex.org/W4280495226","https://openalex.org/W4384155732","https://openalex.org/W4398193131","https://openalex.org/W4401055959"],"related_works":[],"abstract_inverted_index":{"Auditory":[0],"attention":[1,162],"detection":[2,31],"(AAD)":[3],"aims":[4],"to":[5,158,193],"identify":[6],"the":[7,81,94,142,185,194],"attended":[8],"speaker":[9],"in":[10,29,38],"multi-talker":[11],"environments":[12],"by":[13,189],"analyzing":[14],"brain":[15,48],"activity":[16],"recorded":[17],"through":[18],"neural":[19],"monitoring":[20],"techniques.":[21],"Recent":[22],"AAD":[23,176],"approaches":[24],"have":[25],"achieved":[26],"great":[27],"progress":[28],"improving":[30],"accuracy.":[32],"However,":[33],"they":[34],"still":[35],"face":[36],"challenges":[37],"capturing":[39],"complex":[40,128],"spatio-temporal":[41],"dependencies":[42,118],"and":[43,75,87,101,122,152],"high-order":[44,97,116],"nonlinear":[45],"relationships":[46,98],"across":[47,119],"regions.":[49],"To":[50],"address":[51],"these":[52],"challenges,":[53],"this":[54],"paper":[55],"proposes":[56],"DHGCN,":[57],"a":[58,65,69,76,111,123],"dual":[59],"hypergraph":[60,66,71,82,136],"convolutional":[61],"network":[62],"that":[63,114,126,171],"integrates":[64],"modeling":[67,83,143],"module,":[68,74],"dual-branch":[70],"learning":[72],"(DHGL)":[73],"feature":[77,146],"fusion":[78,147],"module.":[79],"Specifically,":[80],"module":[84,106,148],"constructs":[85],"spatial":[86,112,117,151],"temporal":[88,124,129,153],"hypergraphs":[89],"from":[90,155],"EEG":[91,120],"signals,":[92],"enabling":[93],"representation":[95],"of":[96],"among":[99],"channels":[100],"time":[102],"points.":[103],"The":[104,145],"DHGL":[105],"comprises":[107],"two":[108],"parallel":[109],"branches:":[110],"branch":[113,125,132],"learns":[115],"channels,":[121],"captures":[127],"dependencies.":[130],"Each":[131],"uses":[133],"its":[134],"corresponding":[135],"structure,":[137],"which":[138],"is":[139,198],"established":[140],"during":[141],"phase.":[144],"then":[149],"aggregates":[150],"representations":[154],"both":[156],"branches":[157],"support":[159],"robust":[160],"auditory":[161],"classification.":[163],"Extensive":[164],"experiments":[165],"on":[166],"multiple":[167],"benchmark":[168],"datasets":[169],"demonstrate":[170],"DHGCN":[172],"consistently":[173],"outperforms":[174],"state-of-the-art":[175,195],"models.":[177,196],"It":[178],"achieves":[179],"superior":[180],"classification":[181],"performance":[182],"while":[183],"reducing":[184],"trainable":[186],"parameters":[187],"count":[188],"over":[190],"50%":[191],"compared":[192],"Code":[197],"available":[199],"at:":[200],"https://github.com/nobody1219/DHGCN.git.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-25T08:17:42.794288","created_date":"2025-10-25T00:00:00"}
