{"id":"https://openalex.org/W4225275192","doi":"https://doi.org/10.3390/rs14092181","title":"A DEM Super-Resolution Reconstruction Network Combining Internal and External Learning","display_name":"A DEM Super-Resolution Reconstruction Network Combining Internal and External Learning","publication_year":2022,"publication_date":"2022-05-02","ids":{"openalex":"https://openalex.org/W4225275192","doi":"https://doi.org/10.3390/rs14092181"},"language":"en","primary_location":{"id":"doi:10.3390/rs14092181","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14092181","pdf_url":"https://www.mdpi.com/2072-4292/14/9/2181/pdf?version=1651484519","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/9/2181/pdf?version=1651484519","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074887775","display_name":"Xu Lin","orcid":"https://orcid.org/0000-0001-9402-5329"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]},{"id":"https://openalex.org/I4387155973","display_name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection","ror":"https://ror.org/03s7w3c34","country_code":null,"type":"facility","lineage":["https://openalex.org/I31595395","https://openalex.org/I4387155973"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xu Lin","raw_affiliation_strings":["College of Earth Science, Chengdu University of Technology, Chengdu 610059, China","State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]},{"raw_affiliation_string":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu 610059, China","institution_ids":["https://openalex.org/I4387155973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100375544","display_name":"Qingqing Zhang","orcid":"https://orcid.org/0000-0002-5507-466X"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingqing Zhang","raw_affiliation_strings":["College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100666457","display_name":"Hongyue Wang","orcid":"https://orcid.org/0000-0002-3837-9525"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyue Wang","raw_affiliation_strings":["College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112616780","display_name":"Chaolong Yao","orcid":"https://orcid.org/0000-0002-7954-9703"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaolong Yao","raw_affiliation_strings":["College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China"],"affiliations":[{"raw_affiliation_string":"College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101917696","display_name":"Changxin Chen","orcid":"https://orcid.org/0000-0003-1468-5920"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changxin Chen","raw_affiliation_strings":["College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022808269","display_name":"Lin Cheng","orcid":"https://orcid.org/0000-0002-4264-5523"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Cheng","raw_affiliation_strings":["College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003493292","display_name":"Zhaoxiong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoxiong Li","raw_affiliation_strings":["College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5074887775"],"corresponding_institution_ids":["https://openalex.org/I31595395","https://openalex.org/I4387155973"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":2.552,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.90793993,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"14","issue":"9","first_page":"2181","last_page":"2181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","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"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","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/T10531","display_name":"Advanced Vision and Imaging","score":0.998199999332428,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9853000044822693,"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":0.7441093921661377},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5954353213310242},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5758808255195618},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5085088014602661},{"id":"https://openalex.org/keywords/superresolution","display_name":"Superresolution","score":0.4982306957244873},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4843786656856537},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47215911746025085},{"id":"https://openalex.org/keywords/bicubic-interpolation","display_name":"Bicubic interpolation","score":0.45037543773651123},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33347904682159424},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.31270748376846313},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10607227683067322}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7441093921661377},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5954353213310242},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5758808255195618},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5085088014602661},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.4982306957244873},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4843786656856537},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47215911746025085},{"id":"https://openalex.org/C49608258","wikidata":"https://www.wikidata.org/wiki/Q611705","display_name":"Bicubic interpolation","level":4,"score":0.45037543773651123},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33347904682159424},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31270748376846313},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10607227683067322},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C171836373","wikidata":"https://www.wikidata.org/wiki/Q2266329","display_name":"Linear interpolation","level":3,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14092181","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14092181","pdf_url":"https://www.mdpi.com/2072-4292/14/9/2181/pdf?version=1651484519","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:05f54154c2a644a1b9218f47f861c91c","is_oa":true,"landing_page_url":"https://doaj.org/article/05f54154c2a644a1b9218f47f861c91c","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 9, p 2181 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/9/2181/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14092181","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 14; Issue 9; Pages: 2181","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14092181","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14092181","pdf_url":"https://www.mdpi.com/2072-4292/14/9/2181/pdf?version=1651484519","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6700000166893005,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G1010709319","display_name":null,"funder_award_id":"42004013","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G1082888236","display_name":null,"funder_award_id":"SKLGP2021Z022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G195124499","display_name":null,"funder_award_id":"41801389","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2341460573","display_name":null,"funder_award_id":"SKLGP2021Z022","funder_id":"https://openalex.org/F4320326848","funder_display_name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection"},{"id":"https://openalex.org/G3837773280","display_name":null,"funder_award_id":"SKLGP2021Z022","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G4398029709","display_name":null,"funder_award_id":"42004013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4847599610","display_name":null,"funder_award_id":"41801389","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G6433631352","display_name":null,"funder_award_id":"2020YJ0115","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7170797244","display_name":null,"funder_award_id":"2022A1515010469","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8769119774","display_name":null,"funder_award_id":"2020YJ0115","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G993983473","display_name":null,"funder_award_id":"2022A1515010469","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320326848","display_name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4225275192.pdf","grobid_xml":"https://content.openalex.org/works/W4225275192.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W1945855462","https://openalex.org/W2016598597","https://openalex.org/W2058523468","https://openalex.org/W2061225400","https://openalex.org/W2062811295","https://openalex.org/W2092924074","https://openalex.org/W2121264346","https://openalex.org/W2199836608","https://openalex.org/W2242218935","https://openalex.org/W2415472909","https://openalex.org/W2534320940","https://openalex.org/W2579976313","https://openalex.org/W2806558044","https://openalex.org/W2892841407","https://openalex.org/W2916813082","https://openalex.org/W2961686430","https://openalex.org/W2963372104","https://openalex.org/W2963704386","https://openalex.org/W2998414784","https://openalex.org/W3095132671","https://openalex.org/W3108060490","https://openalex.org/W3133192040","https://openalex.org/W3158506795"],"related_works":["https://openalex.org/W2785996895","https://openalex.org/W2074682865","https://openalex.org/W3088281185","https://openalex.org/W2990636717","https://openalex.org/W4389989350","https://openalex.org/W3166902592","https://openalex.org/W3049172720","https://openalex.org/W3094967876","https://openalex.org/W3041957019","https://openalex.org/W4226296458"],"abstract_inverted_index":{"The":[0,77,195,225,283],"study":[1],"of":[2,14,35,84,88,104,110,125,153,168,176,190,201,211,227,261,266,296,304,311,320],"digital":[3],"elevation":[4,285],"model":[5,147,160],"(DEM)":[6],"super-resolution":[7,23,55,68,74,218,228,263],"reconstruction":[8,24,56,69,75,219,229,264],"algorithms":[9],"has":[10],"solved":[11],"the":[12,15,21,36,62,82,92,101,105,111,123,134,145,150,154,159,166,169,173,191,198,202,208,212,222,231,249,258,262,267,288,297,305,312,321],"problem":[13,162],"need":[16],"for":[17,133],"high-resolution":[18],"DEMs.":[19],"However,":[20],"DEM":[22,37,54,112,192,204,213],"algorithm":[25],"itself":[26],"is":[27,41,58,79,117,131,291],"an":[28,42,95],"inverse":[29],"problem,":[30],"and":[31,71,119,156,215,248,257,279,315],"making":[32],"full":[33],"use":[34],"a":[38,52,85,107,126],"priori":[39],"information":[40,90],"effective":[43],"way":[44],"to":[45,99,148,157],"solve":[46,158],"this":[47,253],"problem.":[48],"In":[49],"our":[50],"work,":[51],"new":[53,250],"method":[57,78,251],"proposed":[59],"based":[60,80,120,143],"on":[61,81,121,144],"complementary":[63],"relationship":[64],"between":[65],"internally":[66],"learned":[67,73,177],"methods":[70,269],"externally":[72],"methods.":[76],"presence":[83],"large":[86],"amount":[87],"repetitive":[89],"within":[91],"DEM.":[93],"Using":[94],"internal":[96,102,199],"learning":[97,129,142,189],"approach":[98],"learn":[100],"prior":[103,193,200,210],"DEM,":[106],"low-resolution":[108],"dataset":[109,214],"rich":[113],"in":[114,180,185,221,252],"detailed":[115,178],"features":[116,179],"generated,":[118],"this,":[122],"training":[124],"constrained":[127],"external":[128,209],"network":[130,146,155,182,196],"constructed":[132],"discrepancy":[135],"data":[136],"pair.":[137],"Finally,":[138],"it":[139],"introduces":[140],"residual":[141],"accelerate":[149],"operation":[151],"rate":[152],"degradation":[161],"brought":[163],"about":[164],"by":[165,230],"deepening":[167],"network.":[170],"This":[171],"enables":[172],"better":[174,217,293,301,308,317],"transfer":[175],"deeper":[181],"mappings,":[183],"which":[184],"turn":[186],"ensures":[187],"accurate":[188],"information.":[194],"utilizes":[197],"specific":[203],"as":[205,207],"well":[206],"achieves":[216],"results":[220,226,265],"experimental":[223],"results.":[224],"Bicubic":[232,298],"method,":[233,299,314],"Super-Resolution":[234,245],"Convolutional":[235],"Neural":[236],"Networks":[237],"(SRCNN),":[238],"very":[239],"deep":[240],"convolutional":[241],"networks":[242,246],"(VDSR),":[243],"\u201dZero-Shot\u201d":[244],"(ZSSR)":[247],"paper":[254],"were":[255,270],"compared,":[256],"average":[259],"RMSE":[260],"five":[268],"8.48":[271],"m,":[272,274,276,281],"8.30":[273],"8.09":[275],"7.02":[277],"m":[278],"6.65":[280],"respectively.":[282],"mean":[284],"error":[286],"at":[287],"same":[289],"resolution":[290],"21.6%":[292],"than":[294,302,309,318],"that":[295,303,310,319],"19.9%":[300],"SRCNN,":[306],"17.8%":[307],"VDSR":[313],"5.3%":[316],"ZSSR":[322],"method.":[323]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2022-05-04T00:00:00"}
