{"id":"https://openalex.org/W2986553640","doi":"https://doi.org/10.1109/igarss.2019.8899834","title":"Towards Generating Remote Sensing Images of the Far Past","display_name":"Towards Generating Remote Sensing Images of the Far Past","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2986553640","doi":"https://doi.org/10.1109/igarss.2019.8899834","mag":"2986553640"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8899834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899834","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-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/A5039020372","display_name":"Mesay Belete Bejiga","orcid":"https://orcid.org/0000-0003-2683-6589"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Mesay Belete Bejiga","raw_affiliation_strings":["Department of Information Engineering and Computer science, University of Trento, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021389231","display_name":"Farid Melgani","orcid":"https://orcid.org/0000-0001-9745-3732"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Farid Melgani","raw_affiliation_strings":["Department of Information Engineering and Computer science, University of Trento, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5039020372"],"corresponding_institution_ids":["https://openalex.org/I193223587"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26085323,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"9502","last_page":"9505"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12377","display_name":"Digital Humanities and Scholarship","score":0.9593999981880188,"subfield":{"id":"https://openalex.org/subfields/1208","display_name":"Literature and Literary Theory"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12377","display_name":"Digital Humanities and Scholarship","score":0.9593999981880188,"subfield":{"id":"https://openalex.org/subfields/1208","display_name":"Literature and Literary Theory"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9501000046730042,"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":0.7463687062263489},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6773577332496643},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5856883525848389},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5814005732536316},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5459973812103271},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5443309545516968},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4790022075176239},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3259076178073883},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32383352518081665}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7463687062263489},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6773577332496643},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5856883525848389},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5814005732536316},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5459973812103271},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5443309545516968},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4790022075176239},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3259076178073883},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32383352518081665}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2019.8899834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899834","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.unitn.it:11572/250873","is_oa":false,"landing_page_url":"http://hdl.handle.net/11572/250873","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1544201619","https://openalex.org/W1874815121","https://openalex.org/W2125389028","https://openalex.org/W2128977740","https://openalex.org/W2405756170","https://openalex.org/W2479506271","https://openalex.org/W2559655401","https://openalex.org/W2963143316","https://openalex.org/W2963373786","https://openalex.org/W2963567641","https://openalex.org/W2963865839","https://openalex.org/W2964024144","https://openalex.org/W2964313012","https://openalex.org/W6632683562","https://openalex.org/W6678815747","https://openalex.org/W6683074461","https://openalex.org/W6687500345","https://openalex.org/W6713645886","https://openalex.org/W6718379498","https://openalex.org/W6730746255","https://openalex.org/W6733322467","https://openalex.org/W6779669310"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W3176659669","https://openalex.org/W4287115361"],"abstract_inverted_index":{"Text-to-image":[0],"synthesis":[1],"is":[2,47],"a":[3,21,87,92],"research":[4,130],"topic":[5,37],"that":[6],"has":[7],"not":[8],"yet":[9],"been":[10],"addressed":[11],"by":[12,57],"the":[13,39,78,84,125],"remote":[14,63],"sensing":[15,64],"community.":[16],"It":[17],"consists":[18],"in":[19],"learning":[20],"mapping":[22],"from":[23],"text":[24,51],"description":[25],"to":[26,34,48,76,82,112,115,127,132],"image":[27],"pixels.":[28],"In":[29],"this":[30,36,67,134],"paper,":[31],"we":[32,69],"propose":[33],"address":[35],"for":[38],"very":[40],"first":[41],"time.":[42],"More":[43],"specifically,":[44],"our":[45,117],"objective":[46],"convert":[49],"ancient":[50,108],"descriptions":[52],"of":[53,86,91],"geographic":[54],"areas":[55],"written":[56],"past":[58],"explorers":[59],"into":[60],"an":[61,100],"equivalent":[62],"image.":[65],"To":[66],"effect,":[68],"rely":[70],"on":[71],"generative":[72],"adversarial":[73,101],"networks":[74],"(GANs)":[75],"learn":[77],"mapping.":[79],"GANs":[80],"aim":[81],"represent":[83],"distribution":[85],"dataset":[88],"using":[89],"weights":[90],"deep":[93],"neural":[94],"network,":[95],"which":[96,123],"are":[97],"trained":[98],"as":[99],"competition":[102],"between":[103],"two":[104],"networks.":[105],"We":[106],"collected":[107],"texts":[109],"dating":[110],"back":[111],"7":[113],"BC":[114],"train":[116],"network":[118],"and":[119],"obtained":[120],"interesting":[121],"results,":[122],"form":[124],"basis":[126],"highlight":[128],"future":[129],"directions":[131],"advance":[133],"new":[135],"topic.":[136]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
