{"id":"https://openalex.org/W3128311802","doi":"https://doi.org/10.1109/access.2021.3055868","title":"Supervised Fractional-Order Embedding Multiview Canonical Correlation Analysis via Ordinal Label Dequantization for Image Interest Estimation","display_name":"Supervised Fractional-Order Embedding Multiview Canonical Correlation Analysis via Ordinal Label Dequantization for Image Interest Estimation","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3128311802","doi":"https://doi.org/10.1109/access.2021.3055868","mag":"3128311802"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3055868","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3055868","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09343290.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09343290.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087595074","display_name":"M. Matsumoto","orcid":"https://orcid.org/0000-0002-6531-9907"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masanao Matsumoto","raw_affiliation_strings":["Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-6531-9907","affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103129627","display_name":"Naoki Saito","orcid":"https://orcid.org/0000-0001-7611-2461"},"institutions":[{"id":"https://openalex.org/I4210131518","display_name":"National Institute of Technology, Kushiro College","ror":"https://ror.org/03twzfb97","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210120810","https://openalex.org/I4210131518"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoki Saito","raw_affiliation_strings":["Department of Creative Engineering, National Institute of Technology, Kushiro College, Kushiro, Japan"],"raw_orcid":"https://orcid.org/0000-0001-7611-2461","affiliations":[{"raw_affiliation_string":"Department of Creative Engineering, National Institute of Technology, Kushiro College, Kushiro, Japan","institution_ids":["https://openalex.org/I4210131518"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033215072","display_name":"Keisuke Maeda","orcid":"https://orcid.org/0000-0001-8039-3462"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keisuke Maeda","raw_affiliation_strings":["Office of Institutional Research, Hokkaido University, Sapporo, Japan"],"raw_orcid":"https://orcid.org/0000-0001-8039-3462","affiliations":[{"raw_affiliation_string":"Office of Institutional Research, Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009032240","display_name":"Takahiro Ogawa","orcid":"https://orcid.org/0000-0001-5332-8112"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Ogawa","raw_affiliation_strings":["Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan"],"raw_orcid":"https://orcid.org/0000-0001-5332-8112","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"last","author":{"id":null,"display_name":"Miki Haseyama","orcid":"https://orcid.org/0000-0003-1496-1761"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Miki Haseyama","raw_affiliation_strings":["Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan"],"raw_orcid":"https://orcid.org/0000-0003-1496-1761","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.565,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66207664,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"9","issue":null,"first_page":"21810","last_page":"21822"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9843999743461609,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9843999743461609,"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":0.9807000160217285,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9642000198364258,"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/canonical-correlation","display_name":"Canonical correlation","score":0.7797102928161621},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7386350035667419},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6418527960777283},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6259073615074158},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5730198621749878},{"id":"https://openalex.org/keywords/ordinal-data","display_name":"Ordinal data","score":0.5703359842300415},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5582277178764343},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5026736259460449},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4800213873386383},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4232243001461029},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35537105798721313},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23535031080245972},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1418030858039856},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.09942203760147095}],"concepts":[{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.7797102928161621},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7386350035667419},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6418527960777283},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6259073615074158},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5730198621749878},{"id":"https://openalex.org/C85461838","wikidata":"https://www.wikidata.org/wiki/Q7100785","display_name":"Ordinal data","level":2,"score":0.5703359842300415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5582277178764343},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5026736259460449},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4800213873386383},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4232243001461029},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35537105798721313},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23535031080245972},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1418030858039856},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09942203760147095}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3055868","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3055868","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09343290.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:45c1bff0450d4aad92d5c920ab32e6fb","is_oa":true,"landing_page_url":"https://doaj.org/article/45c1bff0450d4aad92d5c920ab32e6fb","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 21810-21822 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3055868","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3055868","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09343290.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2011880453","display_name":"Construction of low-computation and memory-saving convolutional sparse representation technology","funder_award_id":"18K11367","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4515739553","display_name":"Super-MultiModal Human Analysis Platform for Next Generation of Advanced Retrieval","funder_award_id":"17H01744","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3128311802.pdf","grobid_xml":"https://content.openalex.org/works/W3128311802.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W108816716","https://openalex.org/W1523385540","https://openalex.org/W1538601531","https://openalex.org/W1972745197","https://openalex.org/W1975077471","https://openalex.org/W1984990856","https://openalex.org/W1990254753","https://openalex.org/W2001619934","https://openalex.org/W2011390239","https://openalex.org/W2011430131","https://openalex.org/W2025341678","https://openalex.org/W2033823371","https://openalex.org/W2039508219","https://openalex.org/W2045907009","https://openalex.org/W2046589280","https://openalex.org/W2060519623","https://openalex.org/W2062125287","https://openalex.org/W2064188028","https://openalex.org/W2083095455","https://openalex.org/W2096663965","https://openalex.org/W2097117768","https://openalex.org/W2097800384","https://openalex.org/W2098682165","https://openalex.org/W2108101772","https://openalex.org/W2109943925","https://openalex.org/W2112796928","https://openalex.org/W2119821739","https://openalex.org/W2142200228","https://openalex.org/W2151009539","https://openalex.org/W2154872931","https://openalex.org/W2163605009","https://openalex.org/W2165673880","https://openalex.org/W2166817813","https://openalex.org/W2168380057","https://openalex.org/W2187089797","https://openalex.org/W2213883801","https://openalex.org/W2270911673","https://openalex.org/W2461781129","https://openalex.org/W2585179837","https://openalex.org/W2696558239","https://openalex.org/W2736447684","https://openalex.org/W2752197020","https://openalex.org/W2762769322","https://openalex.org/W2786967268","https://openalex.org/W2791418594","https://openalex.org/W2890676320","https://openalex.org/W2898083387","https://openalex.org/W2971726447","https://openalex.org/W2979977536","https://openalex.org/W2982484396","https://openalex.org/W2991439739","https://openalex.org/W3009067269","https://openalex.org/W3023876191","https://openalex.org/W3099920683","https://openalex.org/W4237951138","https://openalex.org/W4239510810","https://openalex.org/W6631216910","https://openalex.org/W6682644385","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2367413540","https://openalex.org/W2013985456","https://openalex.org/W2951564084","https://openalex.org/W4302984940","https://openalex.org/W2776807270","https://openalex.org/W3127253221","https://openalex.org/W1968846550","https://openalex.org/W4387164999","https://openalex.org/W2392685819","https://openalex.org/W2388999970"],"abstract_inverted_index":{"Supervised":[0],"fractional-order":[1,108],"embedding":[2],"multiview":[3,94],"canonical":[4,91],"correlation":[5,92],"analysis":[6],"via":[7],"ordinal":[8,34,56,81,100],"label":[9,35,57,82,101],"dequantization":[10],"(SFEMCCA-OLD)":[11],"for":[12,116,131],"image":[13,132],"interest":[14,133],"estimation":[15,88,134],"is":[16,22,41,59,73,135],"presented":[17],"in":[18],"this":[19,98],"paper.":[20],"SFEMCCA-OLD":[21,130],"a":[23,45,107],"CCA":[24],"method":[25,111],"that":[26,126,138],"realizes":[27],"accurate":[28,69],"integration":[29,70],"of":[30,47,50,55,63,67,71,79,89,129,139],"features":[31,72],"including":[32],"low-dimensional":[33],"features.":[36,95],"In":[37,75,103],"general,":[38],"since":[39],"information":[40,58,83],"lost":[42],"due":[43],"to":[44],"limitation":[46],"the":[48,53,77,80,90,127],"number":[49],"classes,":[51],"i.e.,":[52],"dimension":[54,78],"smaller":[60],"than":[61,137],"those":[62],"other":[64],"features,":[65],"derivation":[66],"highly":[68],"difficult.":[74],"SFEMCCA-OLD,":[76],"can":[84,112],"be":[85],"increased":[86],"by":[87,105],"between":[93],"We":[96],"call":[97],"approach":[99],"dequantization.":[102],"addition,":[104],"introducing":[106],"technique,":[109],"our":[110],"calculate":[113],"optimal":[114],"projections":[115],"noisy":[117],"data":[118],"such":[119],"as":[120],"real":[121],"data.":[122],"Experimental":[123],"results":[124],"show":[125],"accuracy":[128],"better":[136],"recent":[140],"CCA-based":[141],"methods.":[142]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-09T07:52:08.696243","created_date":"2025-10-10T00:00:00"}