{"id":"https://openalex.org/W1981698166","doi":"https://doi.org/10.1109/fuzz-ieee.2014.6891759","title":"A method of remote sensing image auto classification based on interval type-2 fuzzy c-means","display_name":"A method of remote sensing image auto classification based on interval type-2 fuzzy c-means","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W1981698166","doi":"https://doi.org/10.1109/fuzz-ieee.2014.6891759","mag":"1981698166"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2014.6891759","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2014.6891759","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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/A5101778277","display_name":"Xianchuan Yu","orcid":"https://orcid.org/0000-0003-0742-5135"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xianchuan Yu","raw_affiliation_strings":["College of Information Science and Technology, Beijing Normal University, Beijing, China","College of Information Science and Technology Beijing Normal University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"College of Information Science and Technology Beijing Normal University,Beijing,China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065895367","display_name":"Wei Zhou","orcid":"https://orcid.org/0000-0003-0947-3843"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhou","raw_affiliation_strings":["Graduate School of Beijing Normal University, Beijing, China","[Graduate School of Beijing Normal University, Beijing, China]"],"affiliations":[{"raw_affiliation_string":"Graduate School of Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"[Graduate School of Beijing Normal University, Beijing, China]","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100669553","display_name":"Hui He","orcid":"https://orcid.org/0000-0003-0678-4689"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui He","raw_affiliation_strings":["Beijing Normal University, ZhuHai, China","Beijing Normal University, Zhuhai, China"],"affiliations":[{"raw_affiliation_string":"Beijing Normal University, ZhuHai, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"Beijing Normal University, Zhuhai, China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101778277"],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.05860821,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"223","last_page":"228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9991999864578247,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9991999864578247,"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/T12135","display_name":"Fuzzy Systems and Optimization","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/fuzzy-set","display_name":"Fuzzy set","score":0.6630768775939941},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.659934401512146},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6456548571586609},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6068889498710632},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6044260263442993},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5572724342346191},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.5466814041137695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.528276264667511},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.4988822937011719},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4822893440723419},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4261690676212311},{"id":"https://openalex.org/keywords/fuzzy-classification","display_name":"Fuzzy classification","score":0.411812961101532},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2624453008174896}],"concepts":[{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.6630768775939941},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.659934401512146},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6456548571586609},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6068889498710632},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6044260263442993},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5572724342346191},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.5466814041137695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.528276264667511},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.4988822937011719},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4822893440723419},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4261690676212311},{"id":"https://openalex.org/C127385683","wikidata":"https://www.wikidata.org/wiki/Q1475696","display_name":"Fuzzy classification","level":4,"score":0.411812961101532},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2624453008174896},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz-ieee.2014.6891759","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2014.6891759","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1865067283","https://openalex.org/W1935183702","https://openalex.org/W1968026678","https://openalex.org/W1983658296","https://openalex.org/W1986349186","https://openalex.org/W1989907351","https://openalex.org/W2103232511","https://openalex.org/W2103535990","https://openalex.org/W2114883321","https://openalex.org/W2128251760","https://openalex.org/W2132885717","https://openalex.org/W2141178894","https://openalex.org/W2165428266","https://openalex.org/W2319273832","https://openalex.org/W2380116606"],"related_works":["https://openalex.org/W2945382830","https://openalex.org/W4224807364","https://openalex.org/W2596632494","https://openalex.org/W2535986621","https://openalex.org/W1980197432","https://openalex.org/W2382432689","https://openalex.org/W2000612978","https://openalex.org/W4388110928","https://openalex.org/W1483228865","https://openalex.org/W4292434959"],"abstract_inverted_index":{"The":[0],"pattern":[1,20,24,68],"set":[2,69,128],"of":[3,11,54,71,79,88,124,133,182],"a":[4,67,190],"remote":[5,55,134,141,183],"sensing":[6,56,135,142,184],"image":[7,143],"contains":[8],"many":[9],"kinds":[10],"uncertainties.":[12,40],"Uncertain":[13],"information":[14],"can":[15,37,159,178],"create":[16],"imperfect":[17],"expressions":[18],"for":[19],"sets":[21,103],"in":[22,66],"various":[23,108],"recognition":[25],"algorithms,":[26],"such":[27],"as":[28],"clustering":[29,43,60],"algorithms.":[30],"Methods":[31],"based":[32,146],"the":[33,64,86,122,130,139,148,169,180],"fuzzy":[34,99,102,117,127,151,176],"c-means":[35],"algorithm":[36],"manage":[38,179],"some":[39],"As":[41],"soft":[42],"methods,":[44],"They":[45],"are":[46,70],"known":[47],"to":[48,106],"perform":[49],"better":[50],"on":[51,85,147],"auto":[52],"classification":[53,132,144],"images":[57,136,185],"than":[58],"hard":[59],"methods.":[61],"However,":[62],"if":[63],"clusters":[65,163],"different":[72],"density":[73,172],"and":[74,137,164,188],"high":[75],"order":[76],"uncertainty,":[77],"performance":[78],"FCM":[80],"may":[81],"significantly":[82],"vary":[83],"depending":[84],"choice":[87],"fuzzifiers.":[89],"Thus,":[90],"we":[91],"cannot":[92,111],"obtain":[93,160],"satisfactory":[94],"results":[95,154],"by":[96,115],"using":[97],"type-1":[98,116],"set.":[100],"Type-2":[101],"permit":[104],"us":[105],"model":[107,177],"uncertainties":[109,181],"which":[110],"be":[112],"appropriately":[113,187],"managed":[114],"sets.":[118],"This":[119],"paper":[120],"introduces":[121],"theory":[123],"interval":[125,149],"type-2":[126,150,175],"into":[129],"unsupervised":[131],"proposes":[138],"automatic":[140],"method":[145,158],"c-means.":[152],"Experimental":[153],"indicate":[155],"that":[156],"our":[157],"more":[161,165,186,191],"coherent":[162],"accurate":[166],"boundaries":[167],"from":[168],"data":[170],"with":[171],"difference.":[173],"Our":[174],"get":[189],"desirable":[192],"result.":[193]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
