{"id":"https://openalex.org/W2098827518","doi":"https://doi.org/10.1109/fuzz.2003.1206599","title":"Clustering fuzzy sets with application to image database categorization","display_name":"Clustering fuzzy sets with application to image database categorization","publication_year":2004,"publication_date":"2004-03-22","ids":{"openalex":"https://openalex.org/W2098827518","doi":"https://doi.org/10.1109/fuzz.2003.1206599","mag":"2098827518"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz.2003.1206599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz.2003.1206599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03.","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/A5044691751","display_name":"Hichem Frigui","orcid":"https://orcid.org/0000-0002-8281-1629"},"institutions":[{"id":"https://openalex.org/I94658018","display_name":"University of Memphis","ror":"https://ror.org/01cq23130","country_code":"US","type":"education","lineage":["https://openalex.org/I94658018"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"H. Frigui","raw_affiliation_strings":["Department Electrical & Computer Engineering, University of Memphis, USA"],"affiliations":[{"raw_affiliation_string":"Department Electrical & Computer Engineering, University of Memphis, USA","institution_ids":["https://openalex.org/I94658018"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108359223","display_name":"Nozha Boujemaa","orcid":null},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en informatique et en automatique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1326498283"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"N. Boujemaa","raw_affiliation_strings":["INRIA-Rocquencourt, France"],"affiliations":[{"raw_affiliation_string":"INRIA-Rocquencourt, France","institution_ids":["https://openalex.org/I1326498283"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5044691751"],"corresponding_institution_ids":["https://openalex.org/I94658018"],"apc_list":null,"apc_paid":null,"fwci":0.4497,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.7526666,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"2","issue":null,"first_page":"1182","last_page":"1187"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9668999910354614,"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"}},"topics":[{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9668999910354614,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9603000283241272,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9438999891281128,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.6809712052345276},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6664312481880188},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6498512029647827},{"id":"https://openalex.org/keywords/flame-clustering","display_name":"FLAME clustering","score":0.5718308091163635},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5438209176063538},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5225533843040466},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5047777891159058},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4670606553554535},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.4520520865917206},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4441409409046173},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43171918392181396},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4288256764411926},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.39284831285476685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38699623942375183},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.31827694177627563}],"concepts":[{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.6809712052345276},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6664312481880188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6498512029647827},{"id":"https://openalex.org/C44859942","wikidata":"https://www.wikidata.org/wiki/Q5426511","display_name":"FLAME clustering","level":5,"score":0.5718308091163635},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5438209176063538},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5225533843040466},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5047777891159058},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4670606553554535},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.4520520865917206},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4441409409046173},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43171918392181396},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4288256764411926},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.39284831285476685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38699623942375183},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.31827694177627563},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz.2003.1206599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz.2003.1206599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1481142035","https://openalex.org/W1520063650","https://openalex.org/W1533169541","https://openalex.org/W1554018745","https://openalex.org/W1967662813","https://openalex.org/W1987801991","https://openalex.org/W2021667876","https://openalex.org/W2044165635","https://openalex.org/W2058912656","https://openalex.org/W2060907774","https://openalex.org/W2084134149","https://openalex.org/W2085319761","https://openalex.org/W2131687179","https://openalex.org/W2134696840","https://openalex.org/W2138432035","https://openalex.org/W2141803947","https://openalex.org/W2148201400","https://openalex.org/W2154953441","https://openalex.org/W2573934436","https://openalex.org/W2912565176","https://openalex.org/W3017143921","https://openalex.org/W3176049587","https://openalex.org/W4211007335","https://openalex.org/W4254303229","https://openalex.org/W6631181650","https://openalex.org/W6631963490","https://openalex.org/W6647172677","https://openalex.org/W6750171640","https://openalex.org/W6776565550"],"related_works":["https://openalex.org/W2399084168","https://openalex.org/W2892323093","https://openalex.org/W2373741815","https://openalex.org/W2556490192","https://openalex.org/W3071522575","https://openalex.org/W2358058270","https://openalex.org/W2797947728","https://openalex.org/W2352963450","https://openalex.org/W2374506950","https://openalex.org/W2383030695"],"abstract_inverted_index":{"Clustering":[0],"is":[1,51,121,147,201,215],"considered":[2],"as":[3],"one":[4],"of":[5,58,130,139,144,151,158,169,193,197,210],"the":[6,23,56,59,62,71,99,128,152,198],"most":[7],"important":[8],"tools":[9],"to":[10,45,53,88,97,123,206],"organize":[11],"and":[12,49,83,125,136],"analyze":[13],"large":[14],"multimedia":[15],"databases.":[16],"Most":[17],"existing":[18],"clustering":[19,113],"techniques":[20],"assume":[21,69],"that":[22,70],"clusters":[24,60,131,138,157,183],"have":[25],"well-defined":[26],"shapes":[27,175,187],"(spherical":[28],"or":[29],"ellipsoidal).":[30],"Thus,":[31],"they":[32],"are":[33,42],"not":[34],"suitable":[35],"for":[36],"image":[37,214],"database":[38],"categorization":[39],"where":[40,212],"images":[41],"usually":[43],"mapped":[44],"high-dimensional":[46],"feature":[47,63],"vectors,":[48],"it":[50,205],"hard":[52],"even":[54],"guess":[55],"shape":[57],"in":[61,132],"space.":[64],"In":[65],"this":[66,108],"paper,":[67],"we":[68,84,93,106],"high":[72],"dimensional":[73],"object":[74],"signature":[75],"can":[76],"be":[77,177],"modeled":[78,178],"by":[79,166,179,203,217],"a":[80,95,190,208,218],"fuzzy":[81,103,170,219],"set":[82,220],"introduce":[85],"an":[86,133,148,167],"algorithm":[87,200],"cluster":[89,165],"these":[90],"sets.":[91,104,171,194],"First,":[92],"define":[94],"measure":[96,109],"assess":[98],"dissimilarity":[100],"between":[101],"two":[102],"Then,":[105],"integrate":[107],"into":[110],"our":[111],"synchronization-based":[112],"approach.":[114],"The":[115,142,195],"resulting":[116],"algorithm,":[117],"called":[118],"SyMP/sub":[119,145,161],"FD/":[120,146,162],"robust":[122],"noise":[124],"outliers,":[126],"determines":[127],"number":[129,192],"unsupervised":[134],"manner,":[135],"identifies":[137],"arbitrary":[140],"shapes.":[141],"robustness":[143],"intrinsic":[149],"property":[150],"synchronization":[153],"mechanism.":[154],"To":[155],"identify":[156],"various":[159],"shapes,":[160],"models":[163],"each":[164,213],"ensemble":[168],"Clusters":[172],"with":[173,184],"simple":[174],"would":[176,188],"few":[180],"sets":[181],"while":[182],"more":[185],"complex":[186],"require":[189],"larger":[191],"performance":[196],"proposed":[199],"illustrated":[202],"using":[204],"categorize":[207],"collection":[209],"images,":[211],"described":[216],"representing":[221],"its":[222],"color":[223],"distribution.":[224]},"counts_by_year":[{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
