{"id":"https://openalex.org/W2900595774","doi":"https://doi.org/10.1109/igarss.2018.8517442","title":"Super-Resolution of Remote Sensing Images Based on Transferred Generative Adversarial Network","display_name":"Super-Resolution of Remote Sensing Images Based on Transferred Generative Adversarial Network","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2900595774","doi":"https://doi.org/10.1109/igarss.2018.8517442","mag":"2900595774"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8517442","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517442","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","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/A5006773892","display_name":"Wen Ma","orcid":"https://orcid.org/0000-0001-8192-2506"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Ma","raw_affiliation_strings":["Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032116461","display_name":"Zongxu Pan","orcid":"https://orcid.org/0000-0002-5041-3300"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongxu Pan","raw_affiliation_strings":["Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057347296","display_name":"Jiayi Guo","orcid":"https://orcid.org/0000-0002-2272-0450"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayi Guo","raw_affiliation_strings":["Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056766372","display_name":"Bin Lei","orcid":"https://orcid.org/0000-0001-7625-9236"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Lei","raw_affiliation_strings":["Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":2.0535,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.92968202,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1148","last_page":"1151"},"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":0.9976000189781189,"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":0.9922999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7758344411849976},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7674652338027954},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.7003737092018127},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.6450982689857483},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5737770795822144},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5559059381484985},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.529764711856842},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.521321713924408},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.48108598589897156},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.43092548847198486},{"id":"https://openalex.org/keywords/novelty-detection","display_name":"Novelty detection","score":0.41170576214790344},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4026276767253876},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36387866735458374},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.325044184923172},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3245031237602234}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7758344411849976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7674652338027954},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.7003737092018127},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.6450982689857483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5737770795822144},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5559059381484985},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.529764711856842},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.521321713924408},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.48108598589897156},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.43092548847198486},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.41170576214790344},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4026276767253876},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36387866735458374},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.325044184923172},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3245031237602234},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8517442","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517442","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":17,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W935139217","https://openalex.org/W2028790650","https://openalex.org/W2030707839","https://openalex.org/W2150081556","https://openalex.org/W2161516371","https://openalex.org/W2167635673","https://openalex.org/W2359099468","https://openalex.org/W2523714292","https://openalex.org/W2560533888","https://openalex.org/W2621121458","https://openalex.org/W2953346987","https://openalex.org/W2963470893","https://openalex.org/W2964121744","https://openalex.org/W6602211262","https://openalex.org/W6624640001","https://openalex.org/W6683660953"],"related_works":["https://openalex.org/W2888032422","https://openalex.org/W2996316059","https://openalex.org/W4385421777","https://openalex.org/W3178813832","https://openalex.org/W4377980832","https://openalex.org/W2897769091","https://openalex.org/W2971552217","https://openalex.org/W3005996785","https://openalex.org/W4297411772","https://openalex.org/W4226298148"],"abstract_inverted_index":{"Single":[0],"image":[1],"super-resolution":[2],"(SR)":[3],"has":[4],"been":[5],"widely":[6],"studied":[7],"in":[8,81,138],"recent":[9],"years":[10],"as":[11,70,72],"a":[12,22,31,82],"crucial":[13],"technique":[14],"for":[15,25],"remote":[16,26,103,121],"sensing":[17,27,104,122],"applications.":[18,105],"This":[19],"paper":[20],"proposes":[21],"SR":[23,42],"method":[24,48,131],"images":[28],"based":[29],"on":[30,111],"transferred":[32],"generative":[33],"adversarial":[34],"network":[35],"(TGAN).":[36],"Different":[37],"from":[38,51],"the":[39,44,55,63,67,74,88,95,120,129,142,146],"previous":[40],"GAN-based":[41],"approaches,":[43],"novelty":[45],"of":[46,90,97,140],"our":[47,77],"mainly":[49],"reflects":[50],"two":[52],"aspects.":[53],"First,":[54],"batch":[56],"normalization":[57],"layers":[58],"are":[59],"removed":[60],"to":[61,85,102,134],"reduce":[62],"memory":[64],"consumption":[65],"and":[66,116,136,145],"computational":[68],"burden,":[69],"well":[71],"raising":[73],"accuracy.":[75],"Second,":[76],"model":[78,107],"is":[79,94,108,132],"trained":[80,110],"transfer-learning":[83],"fashion":[84],"cope":[86],"with":[87,119],"insufficiency":[89],"training":[91],"data,":[92],"which":[93],"crux":[96],"applying":[98],"deep":[99],"learning":[100],"methods":[101],"The":[106],"firstly":[109],"an":[112],"external":[113],"dataset":[114],"DIV2K":[115],"further":[117],"fine-tuned":[118],"dataset.":[123],"Our":[124],"experimental":[125],"results":[126],"demonstrate":[127],"that":[128],"proposed":[130],"superior":[133],"SRCNN":[135],"SRGAN":[137],"terms":[139],"both":[141],"objective":[143],"evaluation":[144],"subjective":[147],"perspective.":[148]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":8}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
