{"id":"https://openalex.org/W2109312609","doi":"https://doi.org/10.1109/icsmc.2009.5346059","title":"Bayesian Polytope ARTMAP: An ART-based network with two kinds of inner geometry categories","display_name":"Bayesian Polytope ARTMAP: An ART-based network with two kinds of inner geometry categories","publication_year":2009,"publication_date":"2009-10-01","ids":{"openalex":"https://openalex.org/W2109312609","doi":"https://doi.org/10.1109/icsmc.2009.5346059","mag":"2109312609"},"language":"en","primary_location":{"id":"doi:10.1109/icsmc.2009.5346059","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2009.5346059","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Systems, Man and Cybernetics","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/A5032540389","display_name":"Xinpeng L. Liao","orcid":"https://orcid.org/0000-0002-0719-2346"},"institutions":[{"id":"https://openalex.org/I1290463931","display_name":"Southwest Research Institute","ror":"https://ror.org/03tghng59","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1290463931"]},{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Leonardo Liao","raw_affiliation_strings":["Southwest Research Institute of Electronics and Telecommunication Technology, Chengdu, China","Southwest Research Institute of Electronics and Telecommunication Technology, Chengdu 610041, P.R China"],"affiliations":[{"raw_affiliation_string":"Southwest Research Institute of Electronics and Telecommunication Technology, Chengdu, China","institution_ids":["https://openalex.org/I4210110458"]},{"raw_affiliation_string":"Southwest Research Institute of Electronics and Telecommunication Technology, Chengdu 610041, P.R China","institution_ids":["https://openalex.org/I1290463931"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100947298","display_name":"Yongqiang Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]},{"id":"https://openalex.org/I1290463931","display_name":"Southwest Research Institute","ror":"https://ror.org/03tghng59","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1290463931"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Yongqiang Wu","raw_affiliation_strings":["Southwest Research Institute of Electronics and Telecommunication Technology, Chengdu, China","Southwest Research Institute of Electronics and Telecommunication Technology, Chengdu 610041, P.R China"],"affiliations":[{"raw_affiliation_string":"Southwest Research Institute of Electronics and Telecommunication Technology, Chengdu, China","institution_ids":["https://openalex.org/I4210110458"]},{"raw_affiliation_string":"Southwest Research Institute of Electronics and Telecommunication Technology, Chengdu 610041, P.R China","institution_ids":["https://openalex.org/I1290463931"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5032540389"],"corresponding_institution_ids":["https://openalex.org/I1290463931","https://openalex.org/I4210110458"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11570679,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4830","last_page":"4835"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","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/T10320","display_name":"Neural Networks and Applications","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/T10057","display_name":"Face and Expression Recognition","score":0.9922000169754028,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9871000051498413,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/polytope","display_name":"Polytope","score":0.7318822145462036},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6026022434234619},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5779851078987122},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5580092668533325},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5478916764259338},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5289666056632996},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5005936622619629},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4990675449371338},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4762278199195862},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4655244052410126},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.42950206995010376},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.4246724843978882},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4012707471847534},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35491830110549927},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35334843397140503},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.171453058719635}],"concepts":[{"id":"https://openalex.org/C145691206","wikidata":"https://www.wikidata.org/wiki/Q747980","display_name":"Polytope","level":2,"score":0.7318822145462036},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6026022434234619},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5779851078987122},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5580092668533325},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5478916764259338},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5289666056632996},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5005936622619629},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4990675449371338},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4762278199195862},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4655244052410126},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.42950206995010376},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.4246724843978882},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4012707471847534},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35491830110549927},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35334843397140503},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.171453058719635},{"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsmc.2009.5346059","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2009.5346059","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Systems, Man and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6000000238418579,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1950060225","https://openalex.org/W1967011375","https://openalex.org/W1967764809","https://openalex.org/W1977501201","https://openalex.org/W1979828500","https://openalex.org/W1982610692","https://openalex.org/W2005312922","https://openalex.org/W2015857587","https://openalex.org/W2105333549","https://openalex.org/W2142667669","https://openalex.org/W2144219012","https://openalex.org/W2154404901","https://openalex.org/W2166280719","https://openalex.org/W2170684284","https://openalex.org/W2293520499"],"related_works":["https://openalex.org/W2407375987","https://openalex.org/W3049691116","https://openalex.org/W2505726097","https://openalex.org/W2010643158","https://openalex.org/W2106867672","https://openalex.org/W3081214562","https://openalex.org/W4310268968","https://openalex.org/W2950975704","https://openalex.org/W4297815943","https://openalex.org/W2053745677"],"abstract_inverted_index":{"The":[0],"ART-based":[1],"neural":[2],"networks":[3],"summarize":[4],"data":[5,113],"into":[6],"groups":[7],"via":[8],"the":[9,22,29,57,63,70],"use":[10],"of":[11,24,31],"inner":[12],"categories.":[13,54],"A":[14],"category's":[15],"template":[16],"elements":[17],"are":[18],"updated":[19],"incrementally":[20],"in":[21],"light":[23],"new":[25],"evidence":[26],"provided":[27],"by":[28,76],"presentation":[30],"input":[32,64],"patterns.":[33],"In":[34,80],"order":[35],"to":[36,95,112],"reduce":[37],"approximation":[38],"error,":[39],"this":[40],"paper":[41],"proposes":[42],"Bayesian":[43],"Polytope":[44],"ARTMAP":[45],"(BPTAM)":[46],"which":[47,91],"incorporates":[48],"both":[49],"simplex":[50,58],"categories":[51,59,72],"and":[52,89,97,119],"Gaussian":[53,71],"During":[55],"training,":[56],"expand":[60],"only":[61],"towards":[62],"pattern":[65],"without":[66],"category":[67,98],"overlap,":[68],"while":[69],"grow":[73],"or":[74],"shrink":[75],"limiting":[77],"their":[78],"hypervolumes.":[79],"addition,":[81],"BPTAM":[82,93,108],"uses":[83],"Bayes'":[84],"decision":[85],"theory":[86],"for":[87],"learning":[88],"inference,":[90],"makes":[92],"robust":[94],"noise":[96],"overlap.":[99],"Based":[100],"on":[101],"some":[102],"preliminary":[103],"but":[104],"illustrative":[105],"experimental":[106],"results,":[107],"shows":[109],"better":[110],"applicability":[111],"sets":[114],"with":[115],"noise,":[116],"statistical":[117],"overlapping":[118],"irregular":[120],"geometry.":[121]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
