{"id":"https://openalex.org/W2169687790","doi":"https://doi.org/10.1109/iwfhr.2004.26","title":"Classification of Time-Series Data Using a Generative/Discriminative Hybrid","display_name":"Classification of Time-Series Data Using a Generative/Discriminative Hybrid","publication_year":2004,"publication_date":"2004-12-23","ids":{"openalex":"https://openalex.org/W2169687790","doi":"https://doi.org/10.1109/iwfhr.2004.26","mag":"2169687790"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwfhr.2004.26","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5057948105","display_name":"Karim T. Abou\u2013Moustafa","orcid":"https://orcid.org/0000-0003-4486-3804"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]},{"id":"https://openalex.org/I9736820","display_name":"\u00c9cole de Technologie Sup\u00e9rieure","ror":"https://ror.org/0020snb74","country_code":"CA","type":"education","lineage":["https://openalex.org/I49663120","https://openalex.org/I9736820"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"K.T. Abou-Moustafa","raw_affiliation_strings":["CENPARMI, Concordia University, Montreal, Canada","LIVIA, Ecole de Technologie Sup\u00e9rieure, Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"CENPARMI, Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"LIVIA, Ecole de Technologie Sup\u00e9rieure, Montreal, Canada","institution_ids":["https://openalex.org/I9736820"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015410834","display_name":"Mohamed Cheriet","orcid":"https://orcid.org/0000-0002-5246-7265"},"institutions":[{"id":"https://openalex.org/I9736820","display_name":"\u00c9cole de Technologie Sup\u00e9rieure","ror":"https://ror.org/0020snb74","country_code":"CA","type":"education","lineage":["https://openalex.org/I49663120","https://openalex.org/I9736820"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"M. Cheriet","raw_affiliation_strings":["LIVIA, Ecole de Technologie Sup\u00e9rieure, Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"LIVIA, Ecole de Technologie Sup\u00e9rieure, Montreal, Canada","institution_ids":["https://openalex.org/I9736820"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109871644","display_name":"C.Y. Suen","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"C.Y. Suen","raw_affiliation_strings":["CENPARMI, Concordia University, Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"CENPARMI, Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.696,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":17,"citation_normalized_percentile":{"value":0.782503,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":85,"max":86},"biblio":{"volume":null,"issue":null,"first_page":"51","last_page":"56"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9996,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9996,"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/T10320","display_name":"Neural Networks and Applications","score":0.9881,"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":0.9838,"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/discriminative-model","display_name":"Discriminative model","score":0.9168738},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.65620273},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5212027},{"id":"https://openalex.org/keywords/numeral-system","display_name":"Numeral system","score":0.4117291}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9168738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.70735335},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.65620273},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.64098024},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6346307},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.55381095},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5329391},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5212027},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.47868782},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.42044598},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41301978},{"id":"https://openalex.org/C204160518","wikidata":"https://www.wikidata.org/wiki/Q122653","display_name":"Numeral system","level":2,"score":0.4117291},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.17076632},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwfhr.2004.26","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":30,"referenced_works":["https://openalex.org/W109189503","https://openalex.org/W1517108682","https://openalex.org/W1541904034","https://openalex.org/W1563088657","https://openalex.org/W1576520375","https://openalex.org/W1586645951","https://openalex.org/W1594318682","https://openalex.org/W1875673015","https://openalex.org/W1877570817","https://openalex.org/W1882849807","https://openalex.org/W2010778046","https://openalex.org/W2024986448","https://openalex.org/W2039905248","https://openalex.org/W2049633694","https://openalex.org/W2102770307","https://openalex.org/W2108064086","https://openalex.org/W2125838338","https://openalex.org/W2134523851","https://openalex.org/W2137117485","https://openalex.org/W2137944862","https://openalex.org/W2148603752","https://openalex.org/W2149319679","https://openalex.org/W2156163116","https://openalex.org/W2156980782","https://openalex.org/W2157083019","https://openalex.org/W2162995740","https://openalex.org/W2163614729","https://openalex.org/W2164715647","https://openalex.org/W2166473218","https://openalex.org/W2231077521"],"related_works":["https://openalex.org/W4390874210","https://openalex.org/W4386184937","https://openalex.org/W4384918963","https://openalex.org/W4365211920","https://openalex.org/W4241564561","https://openalex.org/W2987280934","https://openalex.org/W2980541498","https://openalex.org/W2751624083","https://openalex.org/W2128027845","https://openalex.org/W2093104230"],"abstract_inverted_index":{"Classification":[0],"of":[1,18,21,94],"time-series":[2,39,60],"data":[3,40,61],"using":[4,72],"discriminative":[5,74],"models":[6,28],"such":[7,29],"as":[8,30],"SVMs":[9],"is":[10],"very":[11],"hard":[12],"due":[13,41],"to":[14,42,55],"the":[15,24,34,57,82,97],"variable":[16,58],"length":[17,59],"this":[19],"type":[20],"data.":[22],"On":[23],"other":[25],"hand":[26],"generative":[27],"HMMs":[31,54],"have":[32],"become":[33],"standard":[35],"tool":[36],"for":[37,85],"modeling":[38],"their":[43],"efficiency.":[44],"This":[45],"paper":[46],"proposes":[47],"a":[48,63],"general":[49],"generative/discriminative":[50],"hybrid":[51,77],"that":[52,67],"uses":[53],"map":[56],"into":[62],"fixed":[64],"p-dimensional":[65],"vector":[66],"can":[68],"be":[69],"easily":[70],"classified":[71],"any":[73],"model.":[75],"The":[76],"system":[78],"was":[79],"tested":[80],"on":[81],"MNIST":[83],"database":[84],"unconstrained":[86],"handwritten":[87],"numerals":[88],"and":[89],"has":[90],"achieved":[91],"an":[92],"improvement":[93],"1.23%":[95],"(on":[96],"test":[98],"set)":[99],"over":[100],"traditional":[101],"2D":[102],"discrete":[103],"HMMs.":[104]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2169687790","counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2024-12-10T02:45:21.748131","created_date":"2016-06-24"}