{"id":"https://openalex.org/W3015914670","doi":"https://doi.org/10.1109/icassp40776.2020.9053741","title":"Exposure Interpolation Via Hybrid Learning","display_name":"Exposure Interpolation Via Hybrid Learning","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015914670","doi":"https://doi.org/10.1109/icassp40776.2020.9053741","mag":"3015914670"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053741","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5005367753","display_name":"Chaobing Zheng","orcid":"https://orcid.org/0000-0002-4305-8697"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaobing Zheng","raw_affiliation_strings":["Wuhan University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100700917","display_name":"Zhengguo Li","orcid":"https://orcid.org/0000-0002-4525-1204"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhengguo Li","raw_affiliation_strings":["Institute for Infocomm Research, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100747787","display_name":"Yi Yang","orcid":"https://orcid.org/0000-0002-4930-7359"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Yang","raw_affiliation_strings":["Wuhan University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068171246","display_name":"Shiqian Wu","orcid":"https://orcid.org/0000-0002-6383-7663"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiqian Wu","raw_affiliation_strings":["Wuhan University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"24","issue":null,"first_page":"2098","last_page":"2102"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement 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/T11019","display_name":"Image Enhancement 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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9997000098228455,"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":0.9991999864578247,"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/deep-learning","display_name":"Deep learning","score":0.7813467979431152},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.7507673501968384},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7172856330871582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7011576294898987},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5441260933876038},{"id":"https://openalex.org/keywords/high-dynamic-range","display_name":"High dynamic range","score":0.5058174133300781},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.504555344581604},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.49571430683135986},{"id":"https://openalex.org/keywords/image-scaling","display_name":"Image scaling","score":0.4927704632282257},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4800504446029663},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.43918660283088684},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43868374824523926},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.42380523681640625},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4032641053199768},{"id":"https://openalex.org/keywords/dynamic-range","display_name":"Dynamic range","score":0.21189546585083008},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0785866379737854}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7813467979431152},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.7507673501968384},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7172856330871582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7011576294898987},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5441260933876038},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.5058174133300781},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.504555344581604},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.49571430683135986},{"id":"https://openalex.org/C27405340","wikidata":"https://www.wikidata.org/wiki/Q440296","display_name":"Image scaling","level":4,"score":0.4927704632282257},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4800504446029663},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.43918660283088684},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43868374824523926},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.42380523681640625},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4032641053199768},{"id":"https://openalex.org/C87133666","wikidata":"https://www.wikidata.org/wiki/Q1161699","display_name":"Dynamic range","level":2,"score":0.21189546585083008},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0785866379737854},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053741","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1622083366","https://openalex.org/W1885185971","https://openalex.org/W1974871520","https://openalex.org/W1976056157","https://openalex.org/W1995031544","https://openalex.org/W2033686334","https://openalex.org/W2069281566","https://openalex.org/W2098691629","https://openalex.org/W2102584639","https://openalex.org/W2143736264","https://openalex.org/W2156009321","https://openalex.org/W2194775991","https://openalex.org/W2242218935","https://openalex.org/W2254039850","https://openalex.org/W2256362396","https://openalex.org/W2293879958","https://openalex.org/W2534320940","https://openalex.org/W2545639194","https://openalex.org/W2575511118","https://openalex.org/W2752849939","https://openalex.org/W2783573276","https://openalex.org/W2784446449","https://openalex.org/W2796438033","https://openalex.org/W2898542970","https://openalex.org/W2929906481","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W4236229596","https://openalex.org/W6639309558","https://openalex.org/W6658891834","https://openalex.org/W6690498163"],"related_works":["https://openalex.org/W2394941659","https://openalex.org/W1498671902","https://openalex.org/W33056850","https://openalex.org/W2465174208","https://openalex.org/W2030667839","https://openalex.org/W2388226938","https://openalex.org/W2081870131","https://openalex.org/W2168060518","https://openalex.org/W2615143519","https://openalex.org/W1915958221"],"abstract_inverted_index":{"Deep":[0],"learning":[1,50,84,92,123,138],"based":[2],"methods":[3,24],"have":[4],"become":[5],"dominant":[6],"solutions":[7],"to":[8,38,54,97,115,126],"many":[9],"image":[10,59,103],"processing":[11],"problems.":[12],"A":[13,47],"natural":[14],"question":[15,41],"would":[16],"be":[17,95,113],"\"Is":[18],"there":[19],"any":[20],"space":[21],"for":[22,60],"conventional":[23,81,106,110],"on":[25],"these":[26],"problems?\"":[27],"In":[28],"this":[29,40],"paper,":[30],"exposure":[31,58],"interpolation":[32],"is":[33,45,52,76,133],"taken":[34],"as":[35],"an":[36,65],"example":[37],"answer":[39,44],"and":[42,82,125],"the":[43,90,99,105,117,121,128,136],"\"Yes\".":[46],"new":[48],"hybrid":[49],"framework":[51,75],"introduced":[53],"interpolate":[55],"a":[56],"medium":[57],"two":[61],"large-exposure-ratio":[62],"images":[63],"from":[64],"emerging":[66],"high":[67],"dynamic":[68],"range":[69],"(HDR)":[70],"video":[71],"capturing":[72],"device.":[73],"The":[74,109],"set":[77],"up":[78],"by":[79,135],"fusing":[80],"deep":[83,91,122,137],"methods.":[85],"Experimental":[86],"results":[87],"indicate":[88],"that":[89],"method":[93,107,111,124],"can":[94,112],"used":[96],"improve":[98],"quality":[100],"of":[101,120,130],"interpolated":[102],"via":[104],"significantly.":[108],"adopted":[114],"increase":[116],"convergence":[118],"speed":[119],"reduce":[127],"number":[129],"samples":[131],"which":[132],"required":[134],"method.":[139],"They":[140],"compensate":[141],"each":[142],"other.":[143]},"counts_by_year":[{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}