{"id":"https://openalex.org/W2999047980","doi":"https://doi.org/10.1109/icmlc48188.2019.8949261","title":"Single-Image Super-Resolution via Multiple Matrix-Valued Kernel Regression","display_name":"Single-Image Super-Resolution via Multiple Matrix-Valued Kernel Regression","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2999047980","doi":"https://doi.org/10.1109/icmlc48188.2019.8949261","mag":"2999047980"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc48188.2019.8949261","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc48188.2019.8949261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Machine Learning and Cybernetics (ICMLC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5028769645","display_name":"Yi Tang","orcid":"https://orcid.org/0000-0003-4006-428X"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Tang","raw_affiliation_strings":["Faculty of Mathematics and Computer Science, Yunnan Minzu University, Kunming, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Computer Science, Yunnan Minzu University, Kunming, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100900506","display_name":"Zuo Jiang","orcid":"https://orcid.org/0000-0003-2530-9189"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuo Jiang","raw_affiliation_strings":["Faculty of Mathematics and Computer Science, Yunnan Minzu University, Kunming, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Computer Science, Yunnan Minzu University, Kunming, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100636763","display_name":"Junhua Chen","orcid":"https://orcid.org/0000-0002-0947-6879"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun-Hua Chen","raw_affiliation_strings":["Key Laboratory of IOT Application Technology of Universities in Yunnan Province, Kunming, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of IOT Application Technology of Universities in Yunnan Province, Kunming, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.17932212,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"32","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":1.0,"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":1.0,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9980000257492065,"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/kernel","display_name":"Kernel (algebra)","score":0.6506855487823486},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.6097370386123657},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.5596595406532288},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.5388239622116089},{"id":"https://openalex.org/keywords/superresolution","display_name":"Superresolution","score":0.504440188407898},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4818224012851715},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4666362404823303},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4500569999217987},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.431894451379776},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41188085079193115},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36012110114097595},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33470624685287476},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.0735940933227539}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6506855487823486},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.6097370386123657},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.5596595406532288},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.5388239622116089},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.504440188407898},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4818224012851715},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4666362404823303},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4500569999217987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.431894451379776},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41188085079193115},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36012110114097595},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33470624685287476},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0735940933227539},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlc48188.2019.8949261","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc48188.2019.8949261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Machine Learning and Cybernetics (ICMLC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W1510073064","https://openalex.org/W1885185971","https://openalex.org/W2011952414","https://openalex.org/W2014677380","https://openalex.org/W2024585293","https://openalex.org/W2050198433","https://openalex.org/W2076063813","https://openalex.org/W2097074225","https://openalex.org/W2115003579","https://openalex.org/W2118963448","https://openalex.org/W2133665775","https://openalex.org/W2148603752","https://openalex.org/W2149669120","https://openalex.org/W2149760002","https://openalex.org/W2150490197","https://openalex.org/W2161516371","https://openalex.org/W2165966284","https://openalex.org/W2196919019","https://openalex.org/W2343734370","https://openalex.org/W2561139386","https://openalex.org/W2737534804","https://openalex.org/W2900492822","https://openalex.org/W3104196124","https://openalex.org/W6602211262","https://openalex.org/W6683660953"],"related_works":["https://openalex.org/W4250542427","https://openalex.org/W2082780921","https://openalex.org/W1517180214","https://openalex.org/W2025517136","https://openalex.org/W634414395","https://openalex.org/W2143529858","https://openalex.org/W2358774654","https://openalex.org/W4367590696","https://openalex.org/W3112636134","https://openalex.org/W2167191464"],"abstract_inverted_index":{"Single-image":[0],"super-resolution":[1,40,97],"focuses":[2],"on":[3],"learning":[4,95],"a":[5,19],"mapping":[6,30],"to":[7,31],"recover":[8],"high-resolution":[9],"images":[10,14],"from":[11],"given":[12],"low-resolution":[13,33],"with":[15],"the":[16,57,68,85,90],"help":[17],"of":[18,21,59,67,71,89],"set":[20],"paired":[22],"images.":[23,34,80],"Matrix-valued":[24],"operators":[25,44,50,61],"serve":[26],"as":[27,45],"an":[28],"efficient":[29],"super-resolve":[32],"However,":[35],"most":[36],"existed":[37],"matrix-valued":[38,43,49,73,93],"based":[39,51,96],"algorithms":[41],"limit":[42],"linear":[46],"mappings.":[47],"Multiple":[48],"algorithm":[52],"is":[53],"introduced":[54],"for":[55],"improving":[56],"performance":[58],"matrix-value":[60],"in":[62],"single-image":[63],"super-resolution.":[64],"Taking":[65],"advantages":[66],"non-linear":[69],"style":[70],"multiple":[72,92],"operators,":[74],"we":[75],"have":[76],"more":[77],"accurate":[78],"super-resolved":[79],"The":[81],"experimental":[82],"results":[83],"show":[84],"efficiency":[86],"and":[87],"effectiveness":[88],"reported":[91],"operator":[94],"algorithm.":[98]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}