{"id":"https://openalex.org/W1979258564","doi":"https://doi.org/10.1177/0037549712445233","title":"Generalized Transport Mean Shift algorithm for ubiquitous intelligence","display_name":"Generalized Transport Mean Shift algorithm for ubiquitous intelligence","publication_year":2012,"publication_date":"2012-05-22","ids":{"openalex":"https://openalex.org/W1979258564","doi":"https://doi.org/10.1177/0037549712445233","mag":"1979258564"},"language":"en","primary_location":{"id":"doi:10.1177/0037549712445233","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0037549712445233","pdf_url":null,"source":{"id":"https://openalex.org/S32573412","display_name":"SIMULATION","issn_l":"0037-5497","issn":["0037-5497","1741-3133"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIMULATION","raw_type":"journal-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/A5049264093","display_name":"Khamron Sunat","orcid":"https://orcid.org/0000-0002-2042-3284"},"institutions":[{"id":"https://openalex.org/I179193067","display_name":"Khon Kaen University","ror":"https://ror.org/03cq4gr50","country_code":"TH","type":"education","lineage":["https://openalex.org/I179193067"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Khamron Sunat","raw_affiliation_strings":["Department of Computer Science, Khon Kaen University, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Khon Kaen University, Thailand","institution_ids":["https://openalex.org/I179193067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065223909","display_name":"Panida Padungweang","orcid":null},"institutions":[{"id":"https://openalex.org/I72091625","display_name":"Ubon Ratchathani University","ror":"https://ror.org/045nemn19","country_code":"TH","type":"education","lineage":["https://openalex.org/I72091625"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Panida Padungweang","raw_affiliation_strings":["Department of Mathematics, Statistic and Computer, Ubon Ratchathani University, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Statistic and Computer, Ubon Ratchathani University, Thailand","institution_ids":["https://openalex.org/I72091625"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031191415","display_name":"Sirapat Chiewchanwattana","orcid":"https://orcid.org/0000-0003-4473-2206"},"institutions":[{"id":"https://openalex.org/I179193067","display_name":"Khon Kaen University","ror":"https://ror.org/03cq4gr50","country_code":"TH","type":"education","lineage":["https://openalex.org/I179193067"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Sirapat Chiewchanwattana","raw_affiliation_strings":["Department of Computer Science, Khon Kaen University, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Khon Kaen University, Thailand","institution_ids":["https://openalex.org/I179193067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06337453,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"88","issue":"10","first_page":"1202","last_page":"1215"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10423","display_name":"Neurobiology and Insect Physiology Research","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10423","display_name":"Neurobiology and Insect Physiology Research","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12321","display_name":"Insect Pheromone Research and Control","score":0.9571999907493591,"subfield":{"id":"https://openalex.org/subfields/1109","display_name":"Insect Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9431999921798706,"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/computer-science","display_name":"Computer science","score":0.711272656917572},{"id":"https://openalex.org/keywords/mean-shift","display_name":"Mean-shift","score":0.6812862753868103},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6610793471336365},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6471621990203857},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5607913136482239},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.497637540102005},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4967721104621887},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.49215906858444214},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.43992146849632263},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40868717432022095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3141469359397888}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.711272656917572},{"id":"https://openalex.org/C48548287","wikidata":"https://www.wikidata.org/wiki/Q6803557","display_name":"Mean-shift","level":3,"score":0.6812862753868103},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6610793471336365},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6471621990203857},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5607913136482239},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.497637540102005},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4967721104621887},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.49215906858444214},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.43992146849632263},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40868717432022095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3141469359397888},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/0037549712445233","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0037549712445233","pdf_url":null,"source":{"id":"https://openalex.org/S32573412","display_name":"SIMULATION","issn_l":"0037-5497","issn":["0037-5497","1741-3133"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIMULATION","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W18661094","https://openalex.org/W1964443764","https://openalex.org/W2022686119","https://openalex.org/W2034768355","https://openalex.org/W2067191022","https://openalex.org/W2080178568","https://openalex.org/W2097998671","https://openalex.org/W2118382442","https://openalex.org/W2129819572","https://openalex.org/W2141240481","https://openalex.org/W2158819362","https://openalex.org/W2164500538","https://openalex.org/W2914584698","https://openalex.org/W3120740533","https://openalex.org/W4245773085","https://openalex.org/W4301409532"],"related_works":["https://openalex.org/W2023748438","https://openalex.org/W2124385053","https://openalex.org/W2169903804","https://openalex.org/W2352790313","https://openalex.org/W2355406465","https://openalex.org/W1024431332","https://openalex.org/W2051318938","https://openalex.org/W4390608645","https://openalex.org/W2137075463","https://openalex.org/W2129731647"],"abstract_inverted_index":{"Much":[0],"research":[1],"has":[2,102],"been":[3],"conducted":[4],"recently":[5],"relating":[6],"to":[7,62,95],"ubiquitous":[8,224],"intelligent":[9,215],"computing.":[10],"Ubiquitous":[11],"intelligence-enabled":[12],"techniques,":[13],"such":[14],"as":[15,51],"clustering":[16,35,124],"and":[17,34,125,146],"image":[18],"segmentation,":[19],"have":[20],"focused":[21],"on":[22,123],"the":[23,38,52,64,76,85,110,115,133,138,162,178,182,186,196,199,205,211],"development":[24],"of":[25,58,66,69,75,84,112,143,161,177,185,204,213],"intelligence":[26],"methodologies.":[27],"In":[28],"this":[29],"paper,":[30],"a":[31,99,103,223],"simultaneous":[32],"mode-seeking":[33,70,187,200],"algorithm":[36,78,120,135,193,207],"called":[37],"Generalized":[39],"Transport":[40],"Mean":[41,86],"Shift":[42,87],"(GTMS)":[43],"was":[44,60,121],"introduced.":[45],"The":[46,55,72,118,128,149,166],"data":[47,106,179,197],"points":[48,180],"were":[49],"designated":[50],"\u2018transporter\u2013trailer\u2019":[53],"characteristic.":[54],"important":[56],"concept":[57],"transportation":[59],"used":[61,97],"solve":[63],"problem":[65,100],"redundant":[67],"computations":[68],"algorithms.":[71],"time":[73,147],"complexity":[74],"GTMS":[77,134,150,192,206],"is":[79,93,154,190],"much":[80],"lower":[81],"than":[82,159,175],"that":[83,101,132,160],"(MS)":[88],"algorithm.":[89,165],"This":[90,189],"means":[91],"it":[92],"able":[94],"be":[96,170],"in":[98,108,141,198,222],"very":[104],"high":[105],"point,":[107],"particular,":[109],"segmentation":[111],"images":[113],"containing":[114],"green":[116,220],"vegetation.":[117],"proposed":[119],"tested":[122],"image-segmentation":[126],"problems.":[127],"experimental":[129],"results":[130],"showed":[131],"improves":[136],"upon":[137],"existing":[139],"algorithms":[140],"terms":[142],"both":[144],"accuracy":[145],"consumption.":[148],"algorithm\u2019s":[151],"highest":[152],"speed":[153],"also":[155],"333.98":[156],"times":[157],"faster":[158],"standard":[163],"MS":[164],"redundancy":[167],"computation":[168],"can":[169],"reduced":[171],"by":[172],"omitting":[173],"more":[174],"90%":[176],"at":[181],"third":[183],"iteration":[184],"process.":[188,201],"because":[191],"mainly":[194],"reduces":[195],"Thus,":[202],"use":[203],"would":[208],"allow":[209],"for":[210,218],"building":[212],"an":[214],"portable":[216],"device":[217],"surveying":[219],"vegetables":[221],"environment.":[225]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
