{"id":"https://openalex.org/W4416555313","doi":"https://doi.org/10.1007/s11063-025-11814-1","title":"A Global Attractor Guided Learning of Parts-based Representation for Image Clustering","display_name":"A Global Attractor Guided Learning of Parts-based Representation for Image Clustering","publication_year":2025,"publication_date":"2025-11-23","ids":{"openalex":"https://openalex.org/W4416555313","doi":"https://doi.org/10.1007/s11063-025-11814-1"},"language":"en","primary_location":{"id":"doi:10.1007/s11063-025-11814-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11814-1","pdf_url":null,"source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/s11063-025-11814-1","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048614139","display_name":"Jingdian Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I24201400","display_name":"Chengdu University of Information Technology","ror":"https://ror.org/01yxwrh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I24201400"]},{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jingdian Yang","raw_affiliation_strings":["Chengdu College of University of Electronic Science and Technology of China, 611731, Chengdu, People\u2019s Republic of China","School of Information and Software Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, People\u2019s Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chengdu College of University of Electronic Science and Technology of China, 611731, Chengdu, People\u2019s Republic of China","institution_ids":["https://openalex.org/I150229711","https://openalex.org/I31595395"]},{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, People\u2019s Republic of China","institution_ids":["https://openalex.org/I150229711","https://openalex.org/I24201400"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109378580","display_name":"Jingye Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I24201400","display_name":"Chengdu University of Information Technology","ror":"https://ror.org/01yxwrh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I24201400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingye Cai","raw_affiliation_strings":["School of Information and Software Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, People\u2019s Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, People\u2019s Republic of China","institution_ids":["https://openalex.org/I150229711","https://openalex.org/I24201400"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048614139"],"corresponding_institution_ids":["https://openalex.org/I150229711","https://openalex.org/I24201400","https://openalex.org/I31595395"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2205927,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"58","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.2513999938964844,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.2513999938964844,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.08569999784231186,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.08500000089406967,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/attractor","display_name":"Attractor","score":0.7013000249862671},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6219000220298767},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.5109000205993652},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.5097000002861023},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4991999864578247},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4390000104904175},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4375999867916107},{"id":"https://openalex.org/keywords/dynamical-systems-theory","display_name":"Dynamical systems theory","score":0.43230000138282776},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4316999912261963},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.42100000381469727}],"concepts":[{"id":"https://openalex.org/C164380108","wikidata":"https://www.wikidata.org/wiki/Q507187","display_name":"Attractor","level":2,"score":0.7013000249862671},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6219000220298767},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5680999755859375},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.5109000205993652},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.5097000002861023},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4991999864578247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4636000096797943},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4390000104904175},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4375999867916107},{"id":"https://openalex.org/C79379906","wikidata":"https://www.wikidata.org/wiki/Q3174497","display_name":"Dynamical systems theory","level":2,"score":0.43230000138282776},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.42100000381469727},{"id":"https://openalex.org/C51544822","wikidata":"https://www.wikidata.org/wiki/Q465274","display_name":"Ordinary differential equation","level":3,"score":0.3977000117301941},{"id":"https://openalex.org/C120822770","wikidata":"https://www.wikidata.org/wiki/Q5156355","display_name":"Competitive learning","level":3,"score":0.3971000015735626},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.37450000643730164},{"id":"https://openalex.org/C8521452","wikidata":"https://www.wikidata.org/wiki/Q203790","display_name":"Connectionism","level":3,"score":0.3718000054359436},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.3571000099182129},{"id":"https://openalex.org/C33962884","wikidata":"https://www.wikidata.org/wiki/Q378637","display_name":"Dynamical system (definition)","level":3,"score":0.34290000796318054},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.32249999046325684},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31679999828338623},{"id":"https://openalex.org/C177973122","wikidata":"https://www.wikidata.org/wiki/Q7860946","display_name":"Types of artificial neural networks","level":4,"score":0.31520000100135803},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.3142000138759613},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.30250000953674316},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C34862557","wikidata":"https://www.wikidata.org/wiki/Q178985","display_name":"Ode","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2953000068664551},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C91873725","wikidata":"https://www.wikidata.org/wiki/Q3445816","display_name":"Function approximation","level":3,"score":0.27950000762939453},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.27649998664855957},{"id":"https://openalex.org/C164752517","wikidata":"https://www.wikidata.org/wiki/Q5570875","display_name":"Global optimization","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2612999975681305},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.2565999925136566}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11063-025-11814-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11814-1","pdf_url":null,"source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11063-025-11814-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11814-1","pdf_url":null,"source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1618067369","https://openalex.org/W1902027874","https://openalex.org/W2017288758","https://openalex.org/W2019464758","https://openalex.org/W2062210787","https://openalex.org/W2066808305","https://openalex.org/W2110096996","https://openalex.org/W2112246162","https://openalex.org/W2121947440","https://openalex.org/W2132538571","https://openalex.org/W2144730066","https://openalex.org/W2145456480","https://openalex.org/W2194775991","https://openalex.org/W2492010876","https://openalex.org/W2570494446","https://openalex.org/W2741786247","https://openalex.org/W2917811495","https://openalex.org/W3088893343","https://openalex.org/W3120427848","https://openalex.org/W3213929680","https://openalex.org/W4225693658","https://openalex.org/W4226380823","https://openalex.org/W4287603417","https://openalex.org/W4296493390","https://openalex.org/W4307234401","https://openalex.org/W4312459443","https://openalex.org/W4322419553","https://openalex.org/W4377290775","https://openalex.org/W4389104986","https://openalex.org/W4392251929","https://openalex.org/W4399761500","https://openalex.org/W4401634064","https://openalex.org/W4402744262","https://openalex.org/W4402756290"],"related_works":[],"abstract_inverted_index":{"Inspired":[0],"by":[1,98,125],"the":[2,33,37,86,135,139,143,149,152,164,175,180,186,190,231,239,253,256,266,281],"parts-based":[3],"representation":[4],"mechanism":[5,228],"in":[6,51,85,221,244,288],"human":[7,87],"neural":[8,18,91,123,153],"cognition,":[9],"Non-negative":[10],"Matrix":[11],"Factorization":[12],"(NMF)":[13],"serves":[14],"as":[15,72,134],"a":[16,90,94,105,120,157,169],"fundamental":[17],"network":[19],"paradigm":[20],"for":[21],"feature":[22],"extraction":[23],"across":[24],"information":[25],"retrieval":[26],"and":[27,54,75,209,265,303],"computer":[28],"vision":[29],"domains.":[30],"However,":[31],"since":[32],"learning":[34,201,205],"rules":[35,206],"of":[36,45,138,151,159,189,234,238,255],"NMF":[38,166,177,263,270],"algorithm":[39,240],"only":[40],"converge":[41,184],"to":[42,62,111,147,183,185,212,251],"local":[43],"minima":[44],"its":[46],"objective":[47],"function,":[48,168],"it":[49],"results":[50,274],"slow":[52],"convergence":[53,150,237],"instability.":[55],"Although":[56],"significant":[57],"improvements":[58],"have":[59,80],"been":[60],"proposed":[61,181,257,282],"address":[63],"these":[64],"problems,":[65],"they":[66],"introduce":[67],"some":[68,261],"other":[69],"problems":[70],"such":[71],"trivial":[73],"solutions":[74],"high":[76],"computational":[77],"cost.":[78],"Studies":[79],"shown":[81],"that":[82,280],"interconnected":[83],"neurons":[84],"brain":[88],"form":[89],"network,":[92],"i.e.,":[93],"dynamical":[95,140],"system":[96],"governed":[97],"ordinary":[99],"differential":[100],"equations":[101],"(ODEs),":[102],"which":[103],"establishes":[104],"nonlinear":[106],"mapping":[107],"from":[108],"external":[109],"inputs":[110],"their":[112],"associated":[113],"attractors.":[114],"In":[115,193],"this":[116,127,194,245],"paper,":[117],"we":[118,130],"propose":[119],"novel":[121],"NMF-based":[122],"model":[124,182],"leveraging":[126],"insight.":[128],"Specifically,":[129],"adopt":[131],"$$sin^2(\\cdot":[132],")$$":[133],"activation":[136],"function":[137],"system,":[141],"enabling":[142],"global":[144,170,187,213],"attractor":[145,171],"property":[146],"guarantee":[148],"model.":[154,258],"By":[155],"imposing":[156],"constraint":[158],"unique":[160],"ODE":[161],"solution":[162],"on":[163,275,295,298,301,305],"original":[165],"cost":[167],"is":[172,241],"embedded":[173],"into":[174],"existing":[176],"framework,":[178],"allowing":[179],"minimum":[188],"dynamic":[191],"system.":[192],"model,":[195],"1)":[196],"Enhanced":[197],"nonlinearity":[198],"strengthens":[199],"part-based":[200],"performance;":[202],"2)":[203],"The":[204,236],"are":[207,249],"non-increasing":[208],"stable,":[210],"converging":[211],"attractors":[214],"with":[215,260,291],"fewer":[216],"iterations,":[217],"greatly":[218],"boosting":[219],"performance":[220,287],"image":[222,289],"analysis;":[223],"3)":[224],"Its":[225],"dynamic,":[226],"multi-layer":[227],"better":[229],"captures":[230],"intrinsic":[232],"structures":[233],"samples.":[235],"also":[242],"analyzed":[243],"paper.":[246],"Extensive":[247],"experiments":[248],"conducted":[250],"demonstrate":[252],"effectiveness":[254],"Compared":[259],"classic":[262],"models":[264],"most":[267],"recently":[268],"developed":[269],"related":[271],"models,":[272],"test":[273],"four":[276],"different":[277],"datasets":[278],"show":[279],"method":[283],"can":[284],"obtain":[285],"state-of-the-art":[286],"clustering":[290],"accuracy":[292],"improvements:":[293],"1.31%":[294],"ORL,":[296],"1.16%":[297,300],"COIL20,":[299],"Caltech101,":[302],"1.15%":[304],"YouTube":[306],"Faces.":[307]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-11-23T00:00:00"}