{"id":"https://openalex.org/W2171394663","doi":"https://doi.org/10.1109/icip.2009.5414459","title":"Random swap EM algorithm for finite mixture models in image segmentation","display_name":"Random swap EM algorithm for finite mixture models in image segmentation","publication_year":2009,"publication_date":"2009-11-01","ids":{"openalex":"https://openalex.org/W2171394663","doi":"https://doi.org/10.1109/icip.2009.5414459","mag":"2171394663"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2009.5414459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5414459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","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/A5055909810","display_name":"Qinpei Zhao","orcid":"https://orcid.org/0000-0002-1765-1171"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Qinpei Zhao","raw_affiliation_strings":["Department of Computer Science, University of Joensuu, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Joensuu, Finland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037259225","display_name":"Ville Hautam\u00e4ki","orcid":"https://orcid.org/0000-0002-5885-0003"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ville Hautamaki","raw_affiliation_strings":["Department of Computer Science, University of Joensuu, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Joensuu, Finland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018962547","display_name":"Ismo K\u00e4rkk\u00e4inen","orcid":null},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]},{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ismo Karkkainen","raw_affiliation_strings":["Institute of Infocomm Research, Agency for Science, Technology and Research, Singapore"],"affiliations":[{"raw_affiliation_string":"Institute of Infocomm Research, Agency for Science, Technology and Research, Singapore","institution_ids":["https://openalex.org/I3005327000","https://openalex.org/I115228651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037846871","display_name":"Pasi Fr\u00e4nti","orcid":"https://orcid.org/0000-0002-9554-2827"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pasi Franti","raw_affiliation_strings":["Department of Computer Science, University of Joensuu, Finland","School of Computer Science, Fudan University, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Joensuu, Finland","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5055909810"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1809,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.8982848,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2397","last_page":"2400"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":1.0,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":1.0,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9751999974250793,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9398999810218811,"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/initialization","display_name":"Initialization","score":0.6963613629341125},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6878937482833862},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.6808522939682007},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6120012998580933},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.605692446231842},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5171553492546082},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4690974950790405},{"id":"https://openalex.org/keywords/maxima","display_name":"Maxima","score":0.44723325967788696},{"id":"https://openalex.org/keywords/hill-climbing","display_name":"Hill climbing","score":0.41787129640579224},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4058961868286133},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34178996086120605},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32500001788139343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31389978528022766},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.21603059768676758},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0956781804561615}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6963613629341125},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6878937482833862},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.6808522939682007},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6120012998580933},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.605692446231842},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5171553492546082},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4690974950790405},{"id":"https://openalex.org/C91528185","wikidata":"https://www.wikidata.org/wiki/Q520952","display_name":"Maxima","level":3,"score":0.44723325967788696},{"id":"https://openalex.org/C135450995","wikidata":"https://www.wikidata.org/wiki/Q820272","display_name":"Hill climbing","level":2,"score":0.41787129640579224},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4058961868286133},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34178996086120605},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32500001788139343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31389978528022766},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.21603059768676758},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0956781804561615},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C52119013","wikidata":"https://www.wikidata.org/wiki/Q50637","display_name":"Art history","level":1,"score":0.0},{"id":"https://openalex.org/C554144382","wikidata":"https://www.wikidata.org/wiki/Q213156","display_name":"Performance art","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2009.5414459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5414459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1585610988","https://openalex.org/W1618045731","https://openalex.org/W1819316285","https://openalex.org/W1966129222","https://openalex.org/W2007463795","https://openalex.org/W2049633694","https://openalex.org/W2053742104","https://openalex.org/W2069416420","https://openalex.org/W2099297832","https://openalex.org/W2114759290","https://openalex.org/W2117853077","https://openalex.org/W2118292158","https://openalex.org/W2140136927","https://openalex.org/W6635035540","https://openalex.org/W7048738093","https://openalex.org/W7071537254"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W2078124810","https://openalex.org/W2368486525","https://openalex.org/W2389184397","https://openalex.org/W2077224612","https://openalex.org/W84255947","https://openalex.org/W2153481672","https://openalex.org/W2041758614","https://openalex.org/W4312864369","https://openalex.org/W2014842417"],"abstract_inverted_index":{"The":[0],"expectation-maximization":[1],"(EM)":[2],"algorithm":[3,18,46,60,99],"is":[4,19],"a":[5,20,56],"popular":[6],"tool":[7],"in":[8,66,75,94,106],"estimating":[9],"model":[10],"parameters,":[11],"especially":[12],"mixture":[13,37,68],"models.":[14,69],"As":[15],"the":[16,34,42,45,48,51,81,84,92,97,120],"EM":[17,59],"hill-climbing":[21],"approach,":[22],"problems":[23,40,65],"such":[24],"as":[25],"local":[26,85],"maxima,":[27],"plateau":[28],"and":[29,47,87,109],"ridges":[30],"may":[31],"appear.":[32],"In":[33],"case":[35],"of":[36,44,50,83],"models,":[38],"these":[39,64],"involve":[41],"initialization":[43],"structure":[49],"data":[52],"set.":[53],"We":[54,115],"propose":[55],"random":[57],"swap":[58],"(RSEM)":[61],"to":[62,91,119],"overcome":[63],"Gaussian":[67],"Random":[70],"swaps":[71],"are":[72],"repeatedly":[73],"performed":[74],"our":[76],"method,":[77],"which":[78],"can":[79],"break":[80],"configuration":[82],"maxima":[86],"other":[88,95,113],"problems.":[89],"Compared":[90],"strategies":[93],"methods,":[96],"proposed":[98],"has":[100],"relative":[101],"improvements":[102],"on":[103],"log-likelihood":[104],"value":[105],"most":[107],"cases":[108],"less":[110],"variance":[111],"than":[112],"algorithms.":[114],"also":[116],"apply":[117],"RSEM":[118],"image":[121],"segmentation":[122],"problem.":[123]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}