{"id":"https://openalex.org/W4416249569","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227678","title":"Modality-Independent Graph Convolutional Networks with Multi-Task and Hybrid cross-attention for Subject-Independent Emotion Recognition","display_name":"Modality-Independent Graph Convolutional Networks with Multi-Task and Hybrid cross-attention for Subject-Independent Emotion Recognition","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416249569","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227678"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5079266572","display_name":"Qiaoli Zhou","orcid":"https://orcid.org/0000-0002-6991-7605"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiaoli Zhou","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,Shenyang,China,110136"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,Shenyang,China,110136","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101565001","display_name":"Jiawen Song","orcid":"https://orcid.org/0000-0002-1818-7884"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawen Song","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,Shenyang,China,110136"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,Shenyang,China,110136","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061759008","display_name":"Qiang Du","orcid":null},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Du","raw_affiliation_strings":["Shenyang University of Technology,School of Electrical Engineering,Shenyang,China,110870"],"affiliations":[{"raw_affiliation_string":"Shenyang University of Technology,School of Electrical Engineering,Shenyang,China,110870","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113904000","display_name":"Li Ke","orcid":"https://orcid.org/0009-0008-9004-3085"},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Ke","raw_affiliation_strings":["Shenyang University of Technology,School of Electrical Engineering,Shenyang,China,110870"],"affiliations":[{"raw_affiliation_string":"Shenyang University of Technology,School of Electrical Engineering,Shenyang,China,110870","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100458737","display_name":"Yi Zhao","orcid":"https://orcid.org/0000-0003-2803-0933"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhao","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,Shenyang,China,110136"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,Shenyang,China,110136","institution_ids":["https://openalex.org/I125904092"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5079266572"],"corresponding_institution_ids":["https://openalex.org/I125904092"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38160381,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9873999953269958,"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"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9873999953269958,"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"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.0008999999845400453,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.0008999999845400453,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/emotion-recognition","display_name":"Emotion recognition","score":0.5817999839782715},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5498999953269958},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4771000146865845},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4747999906539917},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4465000033378601},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4408000111579895},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40369999408721924},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.3650999963283539}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.741599977016449},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.5817999839782715},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.554099977016449},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5498999953269958},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4771000146865845},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4747999906539917},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4465000033378601},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4408000111579895},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41040000319480896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40369999408721924},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3650999963283539},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.27320000529289246},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":37,"referenced_works":["https://openalex.org/W1958932515","https://openalex.org/W2032254851","https://openalex.org/W2129109788","https://openalex.org/W2131274108","https://openalex.org/W2159929956","https://openalex.org/W2750692136","https://openalex.org/W2786768213","https://openalex.org/W2790404832","https://openalex.org/W2919854899","https://openalex.org/W2950978907","https://openalex.org/W2962905870","https://openalex.org/W2963498646","https://openalex.org/W2963631961","https://openalex.org/W2963677766","https://openalex.org/W2963785564","https://openalex.org/W2998583340","https://openalex.org/W3024961463","https://openalex.org/W3038052796","https://openalex.org/W3042586341","https://openalex.org/W3089557188","https://openalex.org/W3134204148","https://openalex.org/W3141797743","https://openalex.org/W3159301005","https://openalex.org/W4225411558","https://openalex.org/W4294975661","https://openalex.org/W4328007250","https://openalex.org/W4367840164","https://openalex.org/W4379233567","https://openalex.org/W4387145989","https://openalex.org/W4388231033","https://openalex.org/W4388574325","https://openalex.org/W4389105052","https://openalex.org/W4390456217","https://openalex.org/W4390577863","https://openalex.org/W4390953182","https://openalex.org/W4394699177","https://openalex.org/W4400275206"],"related_works":[],"abstract_inverted_index":{"Emotion":[0],"recognition":[1,14,128],"is":[2],"essential":[3],"to":[4,30,38,63,87,95],"human-computer":[5],"interaction,":[6],"medical":[7],"diagnosis,":[8],"and":[9,101],"security":[10],"applications.":[11],"Multimodal":[12],"emotion":[13,127],"integrates":[15],"signals":[16],"from":[17,67],"various":[18,68],"sources,":[19],"providing":[20],"an":[21,25],"objective":[22],"reflection":[23],"of":[24,58],"individual\u2019s":[26],"emotional":[27],"state.":[28],"Due":[29],"its":[31],"unique":[32],"architecture,":[33],"GCN":[34,77],"can":[35],"be":[36],"used":[37],"explore":[39],"the":[40,54,97],"structured":[41],"information":[42],"in":[43],"multimodal":[44,51,109],"signals,":[45],"making":[46],"it":[47],"suitable":[48],"for":[49,108],"decoding":[50],"signals.":[52],"However,":[53],"varying":[55],"receptive":[56,85],"fields":[57,86],"GCNs":[59,82],"constrain":[60],"their":[61],"ability":[62],"effectively":[64],"extract":[65],"features":[66],"modalities.":[69],"In":[70],"this":[71],"paper,":[72],"we":[73,91],"suggest":[74],"a":[75,103],"modality-independent":[76],"model":[78,115],"that":[79,132],"assigns":[80],"modality-specific":[81],"with":[83,122],"tailored":[84],"enhance":[88],"performance.":[89],"Additionally,":[90],"use":[92],"multi-task":[93],"learning":[94],"improve":[96],"model\u2019s":[98],"generalization":[99],"capacity":[100],"introduce":[102],"novel":[104],"hybrid":[105],"cross-attention":[106],"mechanism":[107],"data":[110],"fusion.":[111],"We":[112],"assess":[113],"our":[114,133],"on":[116,138],"two":[117],"datasets":[118],"through":[119],"subject-independent":[120],"tests,":[121],"each":[123],"dataset":[124],"comprising":[125],"numerous":[126],"tasks.Experimental":[129],"findings":[130],"indicate":[131],"methodology":[134],"attains":[135],"outstanding":[136],"results":[137],"both":[139],"datasets.":[140]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}
