{"id":"https://openalex.org/W7130837710","doi":"https://doi.org/10.31449/inf.v50i7.10282","title":"Mutual Information-Based Feature Facet Clustering with Ensemble SVM for fMRI Visual Object Decoding","display_name":"Mutual Information-Based Feature Facet Clustering with Ensemble SVM for fMRI Visual Object Decoding","publication_year":2026,"publication_date":"2026-02-21","ids":{"openalex":"https://openalex.org/W7130837710","doi":"https://doi.org/10.31449/inf.v50i7.10282"},"language":null,"primary_location":{"id":"doi:10.31449/inf.v50i7.10282","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i7.10282","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/10282/6511","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.informatica.si/index.php/informatica/article/download/10282/6511","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124068689","display_name":"Lina Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122526","display_name":"Xi'an Siyuan University","ror":"https://ror.org/02nddbr13","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210122526"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lina Gong","raw_affiliation_strings":["College of Electronic Information Engineering, Xi\u2019an Siyuan University Xi\u2019an 710038, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Information Engineering, Xi\u2019an Siyuan University Xi\u2019an 710038, Shaanxi, China","institution_ids":["https://openalex.org/I4210122526"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5124068689"],"corresponding_institution_ids":["https://openalex.org/I4210122526"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18813777,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"50","issue":"7","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.7253000140190125,"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/T11094","display_name":"Face Recognition and Perception","score":0.7253000140190125,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.05209999904036522,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.029999999329447746,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6919999718666077},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6187999844551086},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5910999774932861},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.4867999851703644},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4733000099658966},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.43320000171661377},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.39739999175071716},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.37220001220703125},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.36329999566078186}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7490000128746033},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7150999903678894},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6919999718666077},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6187999844551086},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5910999774932861},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.4867999851703644},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4733000099658966},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.43320000171661377},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.37220001220703125},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.36329999566078186},{"id":"https://openalex.org/C2779345533","wikidata":"https://www.wikidata.org/wiki/Q75785","display_name":"Visual cortex","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.35409998893737793},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.34610000252723694},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33329999446868896},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.27709999680519104},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.26339998841285706},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.31449/inf.v50i7.10282","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i7.10282","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/10282/6511","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.31449/inf.v50i7.10282","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i7.10282","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/10282/6511","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7130837710.pdf","grobid_xml":"https://content.openalex.org/works/W7130837710.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deciphering":[0],"visual":[1,24,100,109,181],"stimuli":[2],"from":[3],"fMRI":[4,96],"data":[5],"presents":[6],"a":[7,16,30,173],"significant":[8],"challenge":[9],"in":[10],"computational":[11],"neuroscience.":[12],"This":[13],"paper":[14],"introduces":[15],"novel,":[17],"optimized":[18,78],"ensemble":[19,48],"learning":[20],"framework":[21],"for":[22,180],"high-accuracy":[23],"object":[25],"recognition.":[26],"Our":[27],"method":[28,171],"employs":[29],"mutual":[31],"information-based":[32],"hierarchical":[33],"clustering":[34],"technique":[35],"to":[36,84],"automatically":[37],"segment":[38],"the":[39,62,65,69,80,139],"high-dimensional":[40],"voxel":[41],"space":[42],"into":[43],"independent":[44],"feature":[45],"facets.":[46,60],"An":[47],"of":[49,67,145],"Support":[50],"Vector":[51],"Machine":[52],"(SVM)":[53],"classifiers":[54],"is":[55],"then":[56],"trained":[57],"on":[58,93,147,150,154],"these":[59],"Crucially,":[61],"entire":[63],"framework\u2014including":[64],"number":[66],"facets,":[68],"fusion":[70],"operator,":[71],"and":[72,106,152,176],"SVM":[73],"parameters":[74],"(C,":[75],"gamma)\u2014is":[76],"globally":[77],"using":[79],"Simulated":[81],"Annealing":[82],"algorithm":[83],"ensure":[85],"peak":[86,129],"performance.":[87],"We":[88],"rigorously":[89],"evaluated":[90],"our":[91,135,170],"approach":[92],"three":[94,126],"public":[95],"datasets:":[97],"DS105":[98],"(8":[99],"objects),":[101],"DS107":[102],"(4":[103],"semantic":[104],"categories),":[105],"DS116":[107],"(2":[108],"oddball":[110],"stimuli).":[111],"The":[112],"proposed":[113],"model":[114,137],"demonstrated":[115],"exceptional":[116],"performance,":[117],"achieving":[118],"mean":[119],"recognition":[120],"accuracies":[121,144],"above":[122],"95%":[123],"across":[124],"all":[125],"datasets,":[127],"with":[128],"subject-level":[130],"accuracy":[131],"reaching":[132],"100%.":[133],"Specifically,":[134],"Ensemble-965":[136],"(using":[138],"detailed":[140],"Talairach":[141],"Atlas)":[142],"attained":[143],"98.6%":[146],"DS105,":[148],"97.5%":[149],"DS107,":[151],"99.4%":[153],"DS116,":[155],"surpassing":[156],"current":[157],"state-of-the-art":[158],"brain":[159,182],"decoding":[160],"methods":[161],"under":[162],"comparable":[163],"validation":[164],"conditions.":[165],"These":[166],"results":[167],"indicate":[168],"that":[169],"provides":[172],"robust,":[174],"accurate,":[175],"highly":[177],"effective":[178],"solution":[179],"decoding.":[183]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-02-22T00:00:00"}
