{"id":"https://openalex.org/W2148394752","doi":"https://doi.org/10.1109/72.363467","title":"Artificial neural networks for feature extraction and multivariate data projection","display_name":"Artificial neural networks for feature extraction and multivariate data projection","publication_year":1995,"publication_date":"1995-03-01","ids":{"openalex":"https://openalex.org/W2148394752","doi":"https://doi.org/10.1109/72.363467","mag":"2148394752","pmid":"https://pubmed.ncbi.nlm.nih.gov/18263314"},"language":"en","primary_location":{"id":"doi:10.1109/72.363467","doi":"https://doi.org/10.1109/72.363467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/72.363467","pdf_url":null,"source":{"id":"https://openalex.org/S42080949","display_name":"IEEE Transactions on Neural Networks","issn_l":"1045-9227","issn":["1045-9227","1941-0093"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W2148394752"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["crossref","pubmed"],"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/A5112614450","display_name":"Jianchang Mao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210085935","display_name":"IBM Research - Almaden","ror":"https://ror.org/005w8dd04","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210085935","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianchang Mao","raw_affiliation_strings":["IBM Almaden Res. Center, San Jose, CA","IBM Almaden Research Center, San Jose, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Almaden Res. Center, San Jose, CA","institution_ids":["https://openalex.org/I4210085935"]},{"raw_affiliation_string":"IBM Almaden Research Center, San Jose, CA, USA","institution_ids":["https://openalex.org/I4210085935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100613677","display_name":"Anil K. Jain","orcid":"https://orcid.org/0000-0002-6369-6995","observed_orcids":["https://orcid.org/0000-0002-6369-6995"]},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A.K. Jain","raw_affiliation_strings":["Department of Computer Science, Michigan State University, East Lansing, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":19.7514,"has_fulltext":false,"cited_by_count":653,"citation_normalized_percentile":{"value":0.9958866,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"6","issue":"2","first_page":"296","last_page":"317"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9907000064849854,"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":0.9907000064849854,"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":0.006599999964237213,"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/T13141","display_name":"Statistical Methods and Applications","score":0.000699999975040555,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-extraction","display_name":"feature extraction","score":0.9399999976158142},{"id":"https://openalex.org/keywords/data-projection","display_name":"data projection","score":0.7879999876022339},{"id":"https://openalex.org/keywords/multivariate-data-visualization","display_name":"multivariate data visualization","score":0.6740000247955322},{"id":"https://openalex.org/keywords/nonlinear-discriminant-analysis","display_name":"nonlinear discriminant analysis","score":0.8790000081062317},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"linear discriminant analysis","score":0.8399999737739563},{"id":"https://openalex.org/keywords/self-organizing-maps","display_name":"self-organizing maps","score":0.8769999742507935},{"id":"https://openalex.org/keywords/nonlinear-projection","display_name":"nonlinear projection","score":0.7910000085830688},{"id":"https://openalex.org/keywords/adaptive-learning-algorithms","display_name":"adaptive learning algorithms","score":0.921999990940094},{"id":"https://openalex.org/keywords/high-dimensional-data","display_name":"high-dimensional data","score":0.722000002861023},{"id":"https://openalex.org/keywords/neural-network-learning-algorithms","display_name":"neural network learning algorithms","score":0.503000020980835}],"concepts":[{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.7355229258537292},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6967537999153137},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6926249265670776},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.675274133682251},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6518627405166626},{"id":"https://openalex.org/C118038509","wikidata":"https://www.wikidata.org/wiki/Q382970","display_name":"Projection pursuit","level":2,"score":0.636018693447113},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6181440353393555},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5737168788909912},{"id":"https://openalex.org/C111168008","wikidata":"https://www.wikidata.org/wiki/Q1136838","display_name":"Self-organizing map","level":3,"score":0.5072040557861328},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4680732488632202},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33881980180740356},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32374727725982666},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2326216995716095},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/72.363467","doi":"https://doi.org/10.1109/72.363467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/72.363467","pdf_url":null,"source":{"id":"https://openalex.org/S42080949","display_name":"IEEE Transactions on Neural Networks","issn_l":"1045-9227","issn":["1045-9227","1941-0093"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks","raw_type":"journal-article"},{"id":"pmid:18263314","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/18263314","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W7299809","https://openalex.org/W22297218","https://openalex.org/W65738273","https://openalex.org/W222764656","https://openalex.org/W1278167707","https://openalex.org/W1491139858","https://openalex.org/W1840019730","https://openalex.org/W1928273700","https://openalex.org/W1956929239","https://openalex.org/W1971747485","https://openalex.org/W1971784203","https://openalex.org/W1991848143","https://openalex.org/W2009642296","https://openalex.org/W2023963201","https://openalex.org/W2026295629","https://openalex.org/W2029051343","https://openalex.org/W2030129920","https://openalex.org/W2049694710","https://openalex.org/W2059998433","https://openalex.org/W2065075098","https://openalex.org/W2069683962","https://openalex.org/W2078626246","https://openalex.org/W2082612735","https://openalex.org/W2091233563","https://openalex.org/W2110882198","https://openalex.org/W2131329059","https://openalex.org/W2134312057","https://openalex.org/W2135346934","https://openalex.org/W2154904842","https://openalex.org/W2156771765","https://openalex.org/W2165746994","https://openalex.org/W2169031976","https://openalex.org/W2319660501","https://openalex.org/W2432567885","https://openalex.org/W3164355881","https://openalex.org/W4238957295","https://openalex.org/W4251731575","https://openalex.org/W4254691425","https://openalex.org/W4311814787"],"related_works":["https://openalex.org/W1840019730","https://openalex.org/W2105951568","https://openalex.org/W2043760168","https://openalex.org/W1533317430","https://openalex.org/W2141800427","https://openalex.org/W1548071774","https://openalex.org/W1908761068","https://openalex.org/W2285857599","https://openalex.org/W117075264","https://openalex.org/W2114902971"],"abstract_inverted_index":{"Classical":[0],"feature":[1,36,104,123,172],"extraction":[2,37,124,173],"and":[3,15,26,38,65,125,153,174,187],"data":[4,17,39,175,193],"projection":[5,70,126,148,176,185],"methods":[6],"have":[7],"been":[8],"well":[9],"studied":[10],"in":[11,95,103,144],"the":[12,99,129,133,145,150,183],"pattern":[13],"recognition":[14],"exploratory":[16],"analysis":[18,56,62],"literature.":[19],"We":[20,165],"propose":[21],"a":[22,44,53,59,66,179],"number":[23],"of":[24,80,101,113,120,136,182],"networks":[25,42,82,115,170],"learning":[27,89],"algorithms":[28,90],"which":[29,91,140],"provide":[30,156],"new":[31,138,157],"or":[32],"alternative":[33],"tools":[34],"for":[35,47,68,160,171],"projection.":[40],"These":[41],"include":[43],"network":[45,67,131,155],"(SAMANN)":[46],"J.W.":[48],"Sammon's":[49,147],"(1969)":[50],"nonlinear":[51,60,69],"projection,":[52],"linear":[54],"discriminant":[55,61],"(LDA)":[57],"network,":[58,64],"(NDA)":[63],"(NP-SOM)":[71],"based":[72,177],"on":[73,178,191],"Kohonen's":[74],"self-organizing":[75],"map.":[76],"A":[77],"common":[78],"attribute":[79],"these":[81,114],"is":[83,141],"that":[84],"they":[85],"all":[86],"employ":[87],"adaptive":[88],"makes":[92],"them":[93],"suitable":[94],"some":[96],"environments":[97],"where":[98],"distribution":[100],"patterns":[102],"space":[105],"changes":[106],"with":[107,195],"respect":[108],"to":[109],"time.":[110],"The":[111],"availability":[112],"also":[116],"facilitates":[117],"hardware":[118],"implementation":[119],"well-known":[121],"classical":[122],"approaches.":[127],"Moreover,":[128],"SAMANN":[130],"offers":[132],"generalization":[134],"ability":[135],"projecting":[137],"data,":[139],"not":[142],"present":[143],"original":[146],"algorithm;":[149],"NDA":[151],"method":[152],"NP-SOM":[154],"powerful":[158],"approaches":[159],"visualizing":[161],"high":[162],"dimensional":[163],"data.":[164],"evaluate":[166],"five":[167],"representative":[168],"neural":[169],"visual":[180],"judgement":[181],"two-dimensional":[184],"maps":[186],"three":[188],"quantitative":[189],"criteria":[190],"eight":[192],"sets":[194],"various":[196],"properties.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":16},{"year":2015,"cited_by_count":19},{"year":2014,"cited_by_count":15},{"year":2013,"cited_by_count":23},{"year":2012,"cited_by_count":22}],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2016-06-24T00:00:00"}
