{"id":"https://openalex.org/W2963226429","doi":"https://doi.org/10.1109/ssci.2017.8280989","title":"Kernel-based generative learning in distortion feature space","display_name":"Kernel-based generative learning in distortion feature space","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2963226429","doi":"https://doi.org/10.1109/ssci.2017.8280989","mag":"2963226429"},"language":"en","primary_location":{"id":"doi:10.1109/ssci.2017.8280989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2017.8280989","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://digitalcommons.uri.edu/ele_facpubs/398","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074257864","display_name":"Bo Tang","orcid":"https://orcid.org/0000-0001-5708-766X"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Tang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013350630","display_name":"Paul M. Baggenstoss","orcid":"https://orcid.org/0000-0002-3739-6104"},"institutions":[{"id":"https://openalex.org/I4210166245","display_name":"Fraunhofer Institute for Communication, Information Processing and Ergonomics","ror":"https://ror.org/05nn0gw40","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210166245","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Paul M. Baggenstoss","raw_affiliation_strings":["Frauhnhofer FKIE, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Frauhnhofer FKIE, Germany","institution_ids":["https://openalex.org/I4210166245"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100411297","display_name":"Haibo He","orcid":"https://orcid.org/0000-0002-5247-9370"},"institutions":[{"id":"https://openalex.org/I17626003","display_name":"University of Rhode Island","ror":"https://ror.org/013ckk937","country_code":"US","type":"education","lineage":["https://openalex.org/I17626003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haibo He","raw_affiliation_strings":["Department of Electrical Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI","institution_ids":["https://openalex.org/I17626003"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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":0.29029638,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9952999949455261,"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":0.9952999949455261,"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/T11309","display_name":"Music and Audio Processing","score":0.9943000078201294,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.992900013923645,"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/discriminative-model","display_name":"Discriminative model","score":0.7694791555404663},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7473959922790527},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7461526989936829},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.663063645362854},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.612956702709198},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5208193063735962},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.4966478943824768},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4756942689418793},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.44529208540916443},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.4110981822013855},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2093702256679535}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7694791555404663},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7473959922790527},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7461526989936829},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.663063645362854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.612956702709198},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5208193063735962},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.4966478943824768},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4756942689418793},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.44529208540916443},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.4110981822013855},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2093702256679535},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ssci.2017.8280989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2017.8280989","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"},{"id":"pmh:oai:digitalcommons.uri.edu:ele_facpubs-1397","is_oa":true,"landing_page_url":"https://digitalcommons.uri.edu/ele_facpubs/398","pdf_url":null,"source":{"id":"https://openalex.org/S2764761010","display_name":"Journal of Media Literacy Education","issn_l":"2167-8715","issn":["2167-8715"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310316378","host_organization_name":"National Association for Media Literacy Education","host_organization_lineage":["https://openalex.org/P4310316378"],"host_organization_lineage_names":["National Association for Media Literacy Education"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Electrical, Computer, and Biomedical Engineering Faculty Publications","raw_type":"text"},{"id":"pmh:oai:fraunhofer.de:N-621890","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-621890.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer FKIE","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/409913","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/409913","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":{"id":"pmh:oai:digitalcommons.uri.edu:ele_facpubs-1397","is_oa":true,"landing_page_url":"https://digitalcommons.uri.edu/ele_facpubs/398","pdf_url":null,"source":{"id":"https://openalex.org/S2764761010","display_name":"Journal of Media Literacy Education","issn_l":"2167-8715","issn":["2167-8715"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310316378","host_organization_name":"National Association for Media Literacy Education","host_organization_lineage":["https://openalex.org/P4310316378"],"host_organization_lineage_names":["National Association for Media Literacy Education"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Electrical, Computer, and Biomedical Engineering Faculty Publications","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7599999904632568}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337392","display_name":"Division of Electrical, Communications and Cyber Systems","ror":"https://ror.org/01krpsy48"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W102334056","https://openalex.org/W1487808658","https://openalex.org/W1500568346","https://openalex.org/W1603903339","https://openalex.org/W1955617397","https://openalex.org/W1964168965","https://openalex.org/W1984908010","https://openalex.org/W1990579857","https://openalex.org/W2002103521","https://openalex.org/W2031357797","https://openalex.org/W2069303738","https://openalex.org/W2086464933","https://openalex.org/W2095489189","https://openalex.org/W2095858069","https://openalex.org/W2100659887","https://openalex.org/W2112796928","https://openalex.org/W2117489663","https://openalex.org/W2118978333","https://openalex.org/W2125574651","https://openalex.org/W2132103241","https://openalex.org/W2136922672","https://openalex.org/W2148603752","https://openalex.org/W2153464267","https://openalex.org/W2162747531","https://openalex.org/W2163288162","https://openalex.org/W2163779401","https://openalex.org/W2166473218","https://openalex.org/W2171849160","https://openalex.org/W2249181615","https://openalex.org/W2263270445","https://openalex.org/W2343999414","https://openalex.org/W2348210445","https://openalex.org/W2546302380","https://openalex.org/W2797602122","https://openalex.org/W3104298728","https://openalex.org/W3105045783","https://openalex.org/W4254721730","https://openalex.org/W4302161581","https://openalex.org/W6604070940","https://openalex.org/W6674269862","https://openalex.org/W6677619830","https://openalex.org/W6683953743","https://openalex.org/W6684116732","https://openalex.org/W6685032804","https://openalex.org/W7055120948"],"related_works":["https://openalex.org/W2007593166","https://openalex.org/W1603777065","https://openalex.org/W2143234973","https://openalex.org/W2397292208","https://openalex.org/W4221136059","https://openalex.org/W1548677759","https://openalex.org/W2987280934","https://openalex.org/W2751624083","https://openalex.org/W109131529","https://openalex.org/W1503513760"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,12,86],"novel":[4],"kernel-based":[5],"generative":[6,54,92,131,143],"classifier":[7,55,76,93,97,133],"which":[8],"is":[9,28],"defined":[10],"in":[11],"distortion":[13],"subspace":[14],"using":[15],"polynomial":[16],"series":[17],"expansion,":[18],"named":[19],"Kernel-Distortion":[20,132],"(KD)":[21],"classifier.":[22,124],"An":[23],"iterative":[24],"kernel":[25],"selection":[26],"algorithm":[27],"developed":[29],"to":[30,72,114,139],"steadily":[31],"improve":[32,100],"classification":[33,102],"performance":[34,137],"by":[35],"repeatedly":[36],"removing":[37],"and":[38,94,109,118],"adding":[39],"kernels.":[40],"The":[41,81],"experimental":[42],"results":[43,126],"on":[44],"character":[45],"recognition":[46,69,82],"application":[47],"not":[48],"only":[49],"show":[50,127],"that":[51,65,85,128],"the":[52,73,90,95,101,116,119,122,135,140],"proposed":[53,91,123,130],"performs":[56],"better":[57],"than":[58],"many":[59],"existing":[60],"classifiers,":[61],"but":[62],"also":[63],"illustrate":[64],"it":[66],"has":[67,134],"different":[68],"capability":[70],"compared":[71,138],"state-of-the-art":[74],"discriminative":[75,96,148],"\u2014":[77],"deep":[78],"belief":[79],"network.":[80],"diversity":[83,117],"indicates":[84],"hybrid":[87,105],"combination":[88,106],"of":[89,121],"could":[98],"further":[99],"performance.":[103],"Two":[104],"methods,":[107],"cascading":[108],"stacking,":[110],"have":[111],"been":[112],"implemented":[113],"verify":[115],"improvement":[120],"Experimental":[125],"our":[129],"best":[136],"other":[141],"four":[142],"classifiers":[144],"when":[145],"combining":[146],"with":[147],"classifiers.":[149]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}