{"id":"https://openalex.org/W2146670837","doi":"https://doi.org/10.1109/iccv.2007.4409061","title":"Noise Robust Spectral Clustering","display_name":"Noise Robust Spectral Clustering","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2146670837","doi":"https://doi.org/10.1109/iccv.2007.4409061","mag":"2146670837"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2007.4409061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2007.4409061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE 11th International Conference on Computer Vision","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/A5103196797","display_name":"Zhenguo Li","orcid":"https://orcid.org/0000-0002-8492-3069"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenguo Li","raw_affiliation_strings":["Department of Information Engineering, Chinese University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039205892","display_name":"Jianzhuang Liu","orcid":"https://orcid.org/0000-0002-7960-9382"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianzhuang Liu","raw_affiliation_strings":["Department of Information Engineering, Chinese University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019433605","display_name":"Shifeng Chen","orcid":"https://orcid.org/0000-0003-0677-7358"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shifeng Chen","raw_affiliation_strings":["Department of Information Engineering, Chinese University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110380387","display_name":"Xiaoou Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]},{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoou Tang","raw_affiliation_strings":["Department of Information Engineering, Chinese University of Hong Kong, Hong Kong, China","Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103196797"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":2.3014,"has_fulltext":false,"cited_by_count":79,"citation_normalized_percentile":{"value":0.89423151,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9973000288009644,"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/T10057","display_name":"Face and Expression Recognition","score":0.9973000288009644,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9969000220298767,"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":0.9941999912261963,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7976771593093872},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.6962022185325623},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.6281797885894775},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6145505309104919},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.6103897094726562},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5545060038566589},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.524747371673584},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5015304088592529},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.4823424518108368},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4552033543586731},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.45271408557891846},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42633092403411865},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36377954483032227}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7976771593093872},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.6962022185325623},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.6281797885894775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6145505309104919},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.6103897094726562},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5545060038566589},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.524747371673584},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5015304088592529},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.4823424518108368},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4552033543586731},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.45271408557891846},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42633092403411865},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36377954483032227},{"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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":2,"locations":[{"id":"doi:10.1109/iccv.2007.4409061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2007.4409061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE 11th International Conference on Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.309.2522","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.309.2522","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ee.columbia.edu/~zgli/papers/ICCV07_NRSC.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W83404773","https://openalex.org/W658559791","https://openalex.org/W1511160855","https://openalex.org/W1774304772","https://openalex.org/W2034331023","https://openalex.org/W2097645701","https://openalex.org/W2103704311","https://openalex.org/W2105549229","https://openalex.org/W2113592823","https://openalex.org/W2118670840","https://openalex.org/W2121947440","https://openalex.org/W2135674549","https://openalex.org/W2139823104","https://openalex.org/W2149982386","https://openalex.org/W2152322845","https://openalex.org/W2154455818","https://openalex.org/W2160167256","https://openalex.org/W2164021670","https://openalex.org/W2165874743","https://openalex.org/W2166151737","https://openalex.org/W2171009857","https://openalex.org/W3150353689","https://openalex.org/W4285719527","https://openalex.org/W6621858757","https://openalex.org/W6630631696","https://openalex.org/W6638285678","https://openalex.org/W6675685020","https://openalex.org/W6676772307","https://openalex.org/W6677669521","https://openalex.org/W6680434193","https://openalex.org/W6682274981","https://openalex.org/W6682494755","https://openalex.org/W6684102537","https://openalex.org/W6684354137","https://openalex.org/W6684578312","https://openalex.org/W6685061373"],"related_works":["https://openalex.org/W1670332068","https://openalex.org/W2095618524","https://openalex.org/W2347413598","https://openalex.org/W1918542373","https://openalex.org/W71572444","https://openalex.org/W1997383766","https://openalex.org/W2154472250","https://openalex.org/W2350336482","https://openalex.org/W2229352698","https://openalex.org/W2759831793"],"abstract_inverted_index":{"This":[0],"paper":[1],"aims":[2],"to":[3,20,43,92,95,107,115],"introduce":[4],"the":[5,10,22,29,34,47,53,62,69,76,89,93,102,129,139,144,147],"robustness":[6],"against":[7,126],"noise":[8,63,70,127,130],"into":[9,24,134],"spectral":[11,90,117],"clustering":[12,118],"algorithm.":[13],"First,":[14],"we":[15],"propose":[16],"a":[17,25,97],"warping":[18],"model":[19],"map":[21],"data":[23,94,99,158],"new":[26,74,136],"space":[27],"on":[28,154],"basis":[30],"of":[31,78,141,146],"regularization.":[32],"During":[33],"warping,":[35,48],"each":[36],"point":[37],"spreads":[38],"smoothly":[39],"its":[40],"spatial":[41],"information":[42],"other":[44],"points.":[45,71],"After":[46],"empirical":[49],"studies":[50],"show":[51],"that":[52,65,121],"clusters":[54,79,142],"become":[55],"relatively":[56],"compact":[57],"and":[58,143,156],"well":[59],"separated,":[60],"including":[61],"cluster":[64],"is":[66,105,113,124],"formed":[67],"by":[68,83],"In":[72],"this":[73,161],"space,":[75],"number":[77,140],"can":[80],"be":[81],"estimated":[82],"eigenvalue":[84],"analysis.":[85],"We":[86],"further":[87],"apply":[88],"mapping":[91],"obtain":[96],"low-dimensional":[98],"representation.":[100],"Finally,":[101],"K-means":[103],"algorithm":[104,148],"used":[106],"perform":[108],"clustering.":[109],"The":[110],"proposed":[111],"method":[112],"superior":[114],"previous":[116],"methods":[119],"in":[120],"(i)":[122],"it":[123],"robust":[125],"because":[128],"points":[131],"are":[132,149],"grouped":[133],"one":[135],"cluster;":[137],"(ii)":[138],"parameters":[145],"determined":[150],"automatically.":[151],"Experimental":[152],"results":[153],"synthetic":[155],"real":[157],"have":[159],"demonstrated":[160],"superiority.":[162]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":9},{"year":2012,"cited_by_count":7}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
