{"id":"https://openalex.org/W4312447544","doi":"https://doi.org/10.1109/igarss46834.2022.9883144","title":"An Adversarial Training Framework for Sentinel-2 Image Super-Resolution","display_name":"An Adversarial Training Framework for Sentinel-2 Image Super-Resolution","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4312447544","doi":"https://doi.org/10.1109/igarss46834.2022.9883144"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9883144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883144","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 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/A5091309552","display_name":"Matteo Ciotola","orcid":"https://orcid.org/0000-0001-6577-6879"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"M. Ciotola","raw_affiliation_strings":["Universit&#x00E0; Federico II,Dipartimento di Ingegneria Elettrica e delle Tecnologie dell&#x0027;Informazione,Napoli (I),80125"],"affiliations":[{"raw_affiliation_string":"Universit&#x00E0; Federico II,Dipartimento di Ingegneria Elettrica e delle Tecnologie dell&#x0027;Informazione,Napoli (I),80125","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027484173","display_name":"Alex Martinelli","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. Martinelli","raw_affiliation_strings":["Universit&#x00E0; Federico II,Dipartimento di Ingegneria Elettrica e delle Tecnologie dell&#x0027;Informazione,Napoli (I),80125"],"affiliations":[{"raw_affiliation_string":"Universit&#x00E0; Federico II,Dipartimento di Ingegneria Elettrica e delle Tecnologie dell&#x0027;Informazione,Napoli (I),80125","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055412619","display_name":"Antonio Mazza","orcid":"https://orcid.org/0000-0002-7961-1669"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. Mazza","raw_affiliation_strings":["Universit&#x00E0; Federico II,Dipartimento di Ingegneria Elettrica e delle Tecnologie dell&#x0027;Informazione,Napoli (I),80125"],"affiliations":[{"raw_affiliation_string":"Universit&#x00E0; Federico II,Dipartimento di Ingegneria Elettrica e delle Tecnologie dell&#x0027;Informazione,Napoli (I),80125","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034757970","display_name":"Giuseppe Scarpa","orcid":"https://orcid.org/0000-0001-6458-9107"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G. Scarpa","raw_affiliation_strings":["Universit&#x00E0; Federico II,Dipartimento di Ingegneria Elettrica e delle Tecnologie dell&#x0027;Informazione,Napoli (I),80125"],"affiliations":[{"raw_affiliation_string":"Universit&#x00E0; Federico II,Dipartimento di Ingegneria Elettrica e delle Tecnologie dell&#x0027;Informazione,Napoli (I),80125","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091309552"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1806,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.52509625,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3782","last_page":"3785"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9998000264167786,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9986000061035156,"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/adversarial-system","display_name":"Adversarial system","score":0.702257513999939},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6253900527954102},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5953418612480164},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.5868089199066162},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.574045717716217},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.56710284948349},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5384359955787659},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46272340416908264},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4351046085357666},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43321627378463745},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3519372344017029},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21133127808570862},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11161825060844421},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06996011734008789}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.702257513999939},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6253900527954102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5953418612480164},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.5868089199066162},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.574045717716217},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.56710284948349},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5384359955787659},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46272340416908264},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4351046085357666},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43321627378463745},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3519372344017029},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21133127808570862},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11161825060844421},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06996011734008789},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss46834.2022.9883144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883144","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:ricerca.uniparthenope.it:11367/119598","is_oa":false,"landing_page_url":"https://hdl.handle.net/11367/119598","pdf_url":null,"source":{"id":"https://openalex.org/S4377196432","display_name":"CINECA IRIS Institutial research information system (Parthenope University of Naples)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I183638586","host_organization_name":"Parthenope University of Naples","host_organization_lineage":["https://openalex.org/I183638586"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2167635673","https://openalex.org/W2171845746","https://openalex.org/W2194775991","https://openalex.org/W2462592242","https://openalex.org/W2536760076","https://openalex.org/W2754256031","https://openalex.org/W2765811365","https://openalex.org/W2794252992","https://openalex.org/W2811414481","https://openalex.org/W2963073614","https://openalex.org/W2974288697","https://openalex.org/W2987046957","https://openalex.org/W2997019934","https://openalex.org/W3036433012","https://openalex.org/W3046020299","https://openalex.org/W3048320860","https://openalex.org/W3098542449","https://openalex.org/W3115223653","https://openalex.org/W3131068743","https://openalex.org/W3166222868","https://openalex.org/W3176572974","https://openalex.org/W3194146876","https://openalex.org/W3207911243","https://openalex.org/W3213530674","https://openalex.org/W4226507018","https://openalex.org/W6685078114","https://openalex.org/W6729966448","https://openalex.org/W6751746117","https://openalex.org/W6780136151","https://openalex.org/W6781611791"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W4206826928","https://openalex.org/W4291897433","https://openalex.org/W3011074480"],"abstract_inverted_index":{"In":[0,75],"this":[1],"work":[2],"is":[3,35],"presented":[4],"a":[5,58],"new":[6],"adversarial":[7],"training":[8,81],"framework":[9],"for":[10,15,44],"deep":[11],"learning":[12],"neural":[13],"networks":[14],"super-resolution":[16],"of":[17,57,66,72],"Sentinel":[18],"2":[19],"images,":[20],"exploiting":[21],"the":[22,42,55,64,79,90],"data":[23],"fusion":[24],"techniques":[25],"on":[26],"10":[27],"and":[28,38,50],"20":[29],"meters":[30],"bands.":[31],"The":[32],"proposed":[33],"scheme":[34,82],"fully":[36],"convolutional":[37],"tries":[39],"to":[40],"answer":[41],"need":[43],"generalization":[45],"in":[46,87],"scale,":[47],"producing":[48],"realistic":[49],"detailed":[51],"accurate":[52],"images.":[53],"Furthermore,":[54],"presence":[56],"<tex":[59],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[60],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathcal{L}_{1}$</tex>":[61],"loss":[62],"limits":[63],"instability":[65],"GAN":[67,80],"training,":[68],"limiting":[69],"possible":[70],"problems":[71],"spectral":[73],"dis-tortion.":[74],"our":[76],"preliminary":[77],"experiments,":[78],"has":[83],"shown":[84],"comparable":[85],"results":[86],"comparison":[88],"with":[89],"baseline":[91],"approach.":[92]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}