{"id":"https://openalex.org/W2131451769","doi":"https://doi.org/10.1109/nnsp.2002.1030028","title":"Kernel-based topographic map formation achieved with normalized Gaussian competition","display_name":"Kernel-based topographic map formation achieved with normalized Gaussian competition","publication_year":2003,"publication_date":"2003-06-25","ids":{"openalex":"https://openalex.org/W2131451769","doi":"https://doi.org/10.1109/nnsp.2002.1030028","mag":"2131451769"},"language":"en","primary_location":{"id":"doi:10.1109/nnsp.2002.1030028","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nnsp.2002.1030028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing","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/A5022490304","display_name":"Marc M. Van Hulle","orcid":"https://orcid.org/0000-0003-1060-7044"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"M.M. Van Hulle","raw_affiliation_strings":["Laboratorium voor Neuro-en Psychofysiologie, K.U. Leuven, Leuven, Belgium","Laboratorium voor Neuro- en Psychofysiologie, Katholieke Univ., Leuven, Belgium"],"affiliations":[{"raw_affiliation_string":"Laboratorium voor Neuro-en Psychofysiologie, K.U. Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]},{"raw_affiliation_string":"Laboratorium voor Neuro- en Psychofysiologie, Katholieke Univ., Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5022490304"],"corresponding_institution_ids":["https://openalex.org/I99464096"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14469507,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"169","last_page":"178"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9980000257492065,"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":0.9980000257492065,"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":0.9894000291824341,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9868000149726868,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7349779009819031},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5714613795280457},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.5417214035987854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5327465534210205},{"id":"https://openalex.org/keywords/topographic-map","display_name":"Topographic map (neuroanatomy)","score":0.5296539664268494},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5079060196876526},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.4773138463497162},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.46501782536506653},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.440273255109787},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.4325483441352844},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37328845262527466},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35987675189971924},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.3308767080307007},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.26903802156448364},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08983924984931946},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.05578121542930603},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.05335432291030884}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7349779009819031},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5714613795280457},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.5417214035987854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5327465534210205},{"id":"https://openalex.org/C134649547","wikidata":"https://www.wikidata.org/wiki/Q7824961","display_name":"Topographic map (neuroanatomy)","level":3,"score":0.5296539664268494},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5079060196876526},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.4773138463497162},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.46501782536506653},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.440273255109787},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.4325483441352844},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37328845262527466},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35987675189971924},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.3308767080307007},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.26903802156448364},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08983924984931946},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.05578121542930603},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.05335432291030884},{"id":"https://openalex.org/C6757342","wikidata":"https://www.wikidata.org/wiki/Q3486606","display_name":"Posterior parietal cortex","level":2,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nnsp.2002.1030028","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nnsp.2002.1030028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing","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":12,"referenced_works":["https://openalex.org/W65738273","https://openalex.org/W1490675643","https://openalex.org/W1979164582","https://openalex.org/W1984083069","https://openalex.org/W2051719061","https://openalex.org/W2052702017","https://openalex.org/W2097810157","https://openalex.org/W2099577980","https://openalex.org/W2131060073","https://openalex.org/W2151521446","https://openalex.org/W4240981432","https://openalex.org/W4255279886"],"related_works":["https://openalex.org/W4379259010","https://openalex.org/W2964366498","https://openalex.org/W2098028537","https://openalex.org/W4221107122","https://openalex.org/W2140869420","https://openalex.org/W2366185040","https://openalex.org/W2364583776","https://openalex.org/W2004616416","https://openalex.org/W2610404083","https://openalex.org/W2382704364"],"abstract_inverted_index":{"A":[0],"new":[1],"learning":[2],"algorithm":[3],"for":[4,47,58],"kernel-based":[5,59],"topographic":[6,28,60],"map":[7,32,61],"formation":[8],"is":[9,45],"introduced.":[10],"The":[11,30],"kernels":[12],"are":[13],"Gaussians,":[14],"and":[15,18,50,53],"their":[16],"centers":[17],"ranges":[19],"individually":[20],"adapted":[21],"so":[22],"as":[23],"to":[24],"yield":[25],"an":[26],"equiprobabilistic":[27],"map.":[29],"converged":[31],"also":[33],"generates":[34],"a":[35],"heteroscedastic":[36],"Gaussian":[37],"mixture":[38],"model":[39],"of":[40],"the":[41],"input":[42],"density.":[43],"This":[44],"verified":[46],"both":[48],"synthetic":[49],"real-world":[51],"examples,":[52],"compared":[54],"with":[55],"other":[56],"algorithms":[57],"formation.":[62]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}