{"id":"https://openalex.org/W7125935295","doi":"https://doi.org/10.1109/smc58881.2025.11342905","title":"Fusing Contextual Clustering with State Space Models for Dzi Beads Image Classification","display_name":"Fusing Contextual Clustering with State Space Models for Dzi Beads Image Classification","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125935295","doi":"https://doi.org/10.1109/smc58881.2025.11342905"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11342905","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342905","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5039373429","display_name":"Jianjun Xia","orcid":"https://orcid.org/0000-0002-0966-0430"},"institutions":[{"id":"https://openalex.org/I140786321","display_name":"Tibet University","ror":"https://ror.org/05petvd47","country_code":"CN","type":"education","lineage":["https://openalex.org/I140786321"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianjun Xia","raw_affiliation_strings":["Xizang University,Tibetan Information Technology Innovative Talent Training Demonstration Base, School of Information Science and Technology,Lhasa,China"],"affiliations":[{"raw_affiliation_string":"Xizang University,Tibetan Information Technology Innovative Talent Training Demonstration Base, School of Information Science and Technology,Lhasa,China","institution_ids":["https://openalex.org/I140786321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124064431","display_name":"Dingguo Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I140786321","display_name":"Tibet University","ror":"https://ror.org/05petvd47","country_code":"CN","type":"education","lineage":["https://openalex.org/I140786321"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingguo Gao","raw_affiliation_strings":["Xizang University,Tibetan Information Technology Innovative Talent Training Demonstration Base, School of Information Science and Technology,Lhasa,China"],"affiliations":[{"raw_affiliation_string":"Xizang University,Tibetan Information Technology Innovative Talent Training Demonstration Base, School of Information Science and Technology,Lhasa,China","institution_ids":["https://openalex.org/I140786321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111996335","display_name":"Songtao Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I140786321","display_name":"Tibet University","ror":"https://ror.org/05petvd47","country_code":"CN","type":"education","lineage":["https://openalex.org/I140786321"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songtao Xu","raw_affiliation_strings":["Xizang University,Tibetan Information Technology Innovative Talent Training Demonstration Base, School of Information Science and Technology,Lhasa,China"],"affiliations":[{"raw_affiliation_string":"Xizang University,Tibetan Information Technology Innovative Talent Training Demonstration Base, School of Information Science and Technology,Lhasa,China","institution_ids":["https://openalex.org/I140786321"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084552923","display_name":"Q. R. Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I140786321","display_name":"Tibet University","ror":"https://ror.org/05petvd47","country_code":"CN","type":"education","lineage":["https://openalex.org/I140786321"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qijun Zhao","raw_affiliation_strings":["Xizang University,Tibetan Information Technology Innovative Talent Training Demonstration Base, School of Information Science and Technology,Lhasa,China"],"affiliations":[{"raw_affiliation_string":"Xizang University,Tibetan Information Technology Innovative Talent Training Demonstration Base, School of Information Science and Technology,Lhasa,China","institution_ids":["https://openalex.org/I140786321"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5039373429"],"corresponding_institution_ids":["https://openalex.org/I140786321"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68660688,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5191","last_page":"5196"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.16680000722408295,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.16680000722408295,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.07490000128746033,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.05640000104904175,"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":0.5026999711990356},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5023999810218811},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4884999990463257},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4641000032424927},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4595000147819519},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4447999894618988},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.39489999413490295},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.39480000734329224}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5633999705314636},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5026999711990356},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5023999810218811},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4884999990463257},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4767000079154968},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4641000032424927},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4595000147819519},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4447999894618988},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.39480000734329224},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.302700012922287},{"id":"https://openalex.org/C72279823","wikidata":"https://www.wikidata.org/wiki/Q1139726","display_name":"Impulse response","level":2,"score":0.2978000044822693},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29089999198913574},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27129998803138733},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2635999917984009}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11342905","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342905","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2618530766","https://openalex.org/W2883780447","https://openalex.org/W2954996726","https://openalex.org/W2963446712","https://openalex.org/W2982083293","https://openalex.org/W3094897602","https://openalex.org/W3138516171","https://openalex.org/W4312443924","https://openalex.org/W4385245566","https://openalex.org/W4386047745","https://openalex.org/W4386076539","https://openalex.org/W4394673925","https://openalex.org/W4401450512","https://openalex.org/W4406047507","https://openalex.org/W4406612778","https://openalex.org/W4410915127","https://openalex.org/W4415796023"],"related_works":[],"abstract_inverted_index":{"The":[0,208],"dzi":[1,66,80,111,160,178,236],"beads":[2,67,81,161,179,237],"pattern":[3],"categories":[4,14],"are":[5,15,100],"rich":[6],"and":[7,9,36,52,96,113,133,155,163,183,195,205,222,227],"diverse,":[8],"the":[10,13,28,50,54,60,65,85,90,105,114,130,136,153,159,165,168,177,184,200,213,231,235],"differences":[11],"between":[12,107,129],"small,":[16],"which":[17,46,192],"leads":[18],"to":[19,58,83,102,125,143,150],"a":[20,43,74,127],"certain":[21],"challenge":[22],"in":[23,120,123,203,218],"its":[24],"classification.":[25],"To":[26],"address":[27],"problems":[29],"of":[30,64,79,89,110,117,135,147,158,167,190,220,224,234],"weak":[31],"generalisation":[32,62,87],"performance,":[33],"low":[34],"accuracy,":[35],"high":[37],"computational":[38,131,225],"complexity,":[39],"this":[40],"paper":[41],"proposes":[42],"FasterVim":[44],"method,":[45],"takes":[47],"FasterNet":[48,70],"as":[49,73],"baseline":[51,75,201],"uses":[53],"designed":[55],"FasterVimBlock":[56],"module":[57],"improve":[59,84,164],"overall":[61,86],"performance":[63,88],"images.":[68],"Firstly,":[69],"is":[71,141,173,193,216],"used":[72],"for":[76],"data":[77],"enhancement":[78],"images":[82,112],"classification":[91,181,239],"model.":[92,137,169,240],"Secondly,":[93],"contextual":[94],"clustering":[95],"state":[97],"space":[98],"models":[99],"fused":[101],"effectively":[103,229],"implement":[104],"interaction":[106],"local":[108,156],"features":[109,119,157],"linear":[115],"representation":[116],"image":[118,162,180,238],"long":[121],"sequences,":[122],"order":[124],"achieve":[126,144],"balance":[128],"complexity":[132],"accuracy":[134,166,189,221],"Next,":[138],"point":[139],"convolution":[140],"introduced":[142],"different":[145],"scales":[146],"channel":[148],"attention":[149],"efficiently":[151],"extract":[152],"global":[154],"Finally,":[170],"experimental":[171,209],"validation":[172],"carried":[174],"out":[175],"on":[176],"dataset,":[182],"proposed":[185,214],"method":[186,215],"achieves":[187],"an":[188],"93.8%,":[191],"1.91%":[194],"1.5":[196],"times":[197],"higher":[198],"than":[199],"model":[202],"Accuracy":[204],"Flops,":[206],"respectively.":[207],"results":[210],"show":[211],"that":[212],"competitive":[217],"terms":[219],"number":[223],"parameters,":[226],"can":[228],"meet":[230],"deployment":[232],"application":[233]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-29T00:00:00"}
