{"id":"https://openalex.org/W2187133255","doi":"https://doi.org/10.1109/lsp.2015.2504121","title":"Joint Learning of Multiple Regressors for Single Image Super-Resolution","display_name":"Joint Learning of Multiple Regressors for Single Image Super-Resolution","publication_year":2015,"publication_date":"2015-11-26","ids":{"openalex":"https://openalex.org/W2187133255","doi":"https://doi.org/10.1109/lsp.2015.2504121","mag":"2187133255"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2015.2504121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2015.2504121","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-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/A5100323983","display_name":"Kai Zhang","orcid":"https://orcid.org/0000-0002-6319-3722"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kai Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013751828","display_name":"Baoquan Wang","orcid":"https://orcid.org/0000-0001-6475-8513"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoquan Wang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636655","display_name":"Wangmeng Zuo","orcid":"https://orcid.org/0000-0002-3330-783X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wangmeng Zuo","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100776513","display_name":"Hongzhi Zhang","orcid":"https://orcid.org/0000-0001-8025-346X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongzhi Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100433899","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-2078-4215"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["Department of Computing, Hong Kong Polytechnic University, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100323983"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":4.4183,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.96417205,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"23","issue":"1","first_page":"102","last_page":"106"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9993000030517578,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9950000047683716,"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/computer-science","display_name":"Computer science","score":0.6312305331230164},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5911542773246765},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.585524320602417},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5370842814445496},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5335607528686523},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.46553176641464233},{"id":"https://openalex.org/keywords/local-regression","display_name":"Local regression","score":0.44477176666259766},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4410322606563568},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.42749685049057007},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.42197349667549133},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4111078679561615},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38549530506134033},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.3382788300514221},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23989412188529968},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.12989699840545654},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.08951419591903687},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08594709634780884}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6312305331230164},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5911542773246765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.585524320602417},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5370842814445496},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5335607528686523},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.46553176641464233},{"id":"https://openalex.org/C60316415","wikidata":"https://www.wikidata.org/wiki/Q6664520","display_name":"Local regression","level":4,"score":0.44477176666259766},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4410322606563568},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.42749685049057007},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.42197349667549133},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4111078679561615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38549530506134033},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.3382788300514221},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23989412188529968},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.12989699840545654},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.08951419591903687},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08594709634780884},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"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/lsp.2015.2504121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2015.2504121","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/65935","is_oa":false,"landing_page_url":"http://hdl.handle.net/10397/65935","pdf_url":null,"source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal/Magazine Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3807605092","display_name":null,"funder_award_id":"61271093","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G790146371","display_name":null,"funder_award_id":"61471146","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W935139217","https://openalex.org/W1539200859","https://openalex.org/W1791560514","https://openalex.org/W1949096787","https://openalex.org/W1973794531","https://openalex.org/W1981536260","https://openalex.org/W1991371637","https://openalex.org/W1995228944","https://openalex.org/W2011277999","https://openalex.org/W2011952414","https://openalex.org/W2025653905","https://openalex.org/W2041844466","https://openalex.org/W2044011870","https://openalex.org/W2047920195","https://openalex.org/W2053186076","https://openalex.org/W2056469638","https://openalex.org/W2064451467","https://openalex.org/W2078431023","https://openalex.org/W2092441942","https://openalex.org/W2097074225","https://openalex.org/W2098506229","https://openalex.org/W2103047572","https://openalex.org/W2113598499","https://openalex.org/W2117865218","https://openalex.org/W2118963448","https://openalex.org/W2121058967","https://openalex.org/W2133665775","https://openalex.org/W2140050933","https://openalex.org/W2150081556","https://openalex.org/W2150884987","https://openalex.org/W2151452149","https://openalex.org/W2163935418","https://openalex.org/W2296458386","https://openalex.org/W2395103039","https://openalex.org/W3104720471","https://openalex.org/W4377561911","https://openalex.org/W6602211262","https://openalex.org/W6624640001","https://openalex.org/W6683680428","https://openalex.org/W6697158745"],"related_works":["https://openalex.org/W1514609475","https://openalex.org/W2947806671","https://openalex.org/W2390878257","https://openalex.org/W1976188970","https://openalex.org/W2990541822","https://openalex.org/W1588885902","https://openalex.org/W2786094008","https://openalex.org/W3131501806","https://openalex.org/W2799683370","https://openalex.org/W2807745940"],"abstract_inverted_index":{"Using":[0],"a":[1,24,32,38,78,118,151],"global":[2],"regression":[3,93],"model":[4,41,57],"for":[5,42],"single":[6],"image":[7],"super-resolution":[8],"(SISR)":[9],"generally":[10],"fails":[11],"to":[12,68,84,114,140,146,155],"produce":[13],"visually":[14],"pleasant":[15],"output.":[16],"The":[17],"recently":[18],"developed":[19],"local":[20,40,56,66,92,105,136],"learning":[21,37,103],"methods":[22,48],"provide":[23],"remedy":[25],"by":[26],"partitioning":[27],"the":[28,49,87,129],"feature":[29,88],"space":[30,50,89],"into":[31],"number":[33,64],"of":[34,65,80,98,121],"clusters":[35],"and":[36,91,104,138],"simple":[39],"each":[43],"cluster.":[44],"However,":[45],"in":[46,61],"these":[47],"partition":[51,90],"is":[52,112],"conducted":[53],"separately":[54],"from":[55],"learning,":[58],"which":[59],"results":[60,126,145],"an":[62],"abundant":[63],"models":[67,137],"achieve":[69,141],"satisfying":[70],"performance.":[71],"To":[72],"address":[73],"this":[74],"problem,":[75],"we":[76],"propose":[77],"mixture":[79],"experts":[81],"(MoE)":[82],"method":[83,131],"jointly":[85],"learn":[86],"models.":[94],"Our":[95],"MoE":[96,116],"consists":[97],"two":[99],"components:":[100],"gating":[101],"network":[102],"regressors":[106],"learning.":[107],"An":[108],"expectation-maximization":[109],"(EM)":[110],"algorithm":[111],"adopted":[113],"train":[115],"on":[117],"large":[119],"set":[120],"LR/HR":[122],"patch":[123],"pairs.":[124],"Experimental":[125],"demonstrate":[127],"that":[128],"proposed":[130],"can":[132],"use":[133],"much":[134],"less":[135],"time":[139],"comparable":[142],"or":[143],"superior":[144],"state-of-the-art":[147],"SISR":[148],"methods,":[149],"providing":[150],"highly":[152],"practical":[153],"solution":[154],"real":[156],"applications.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}