{"id":"https://openalex.org/W3131068743","doi":"https://doi.org/10.1109/igarss39084.2020.9323734","title":"Super-Resolution of Large Volumes of Sentinel-2 Images with High Performance Distributed Deep Learning","display_name":"Super-Resolution of Large Volumes of Sentinel-2 Images with High Performance Distributed Deep Learning","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3131068743","doi":"https://doi.org/10.1109/igarss39084.2020.9323734","mag":"3131068743"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9323734","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323734","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 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/A5101885818","display_name":"Run Zhang","orcid":"https://orcid.org/0000-0003-0278-2256"},"institutions":[{"id":"https://openalex.org/I171892758","display_name":"Forschungszentrum J\u00fclich","ror":"https://ror.org/02nv7yv05","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I171892758"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Run Zhang","raw_affiliation_strings":["J\u00fclich Supercomputing Centre, Forschungszentrum, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J\u00fclich Supercomputing Centre, Forschungszentrum, Germany","institution_ids":["https://openalex.org/I171892758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058680339","display_name":"Gabriele Cavallaro","orcid":"https://orcid.org/0000-0002-3239-9904"},"institutions":[{"id":"https://openalex.org/I171892758","display_name":"Forschungszentrum J\u00fclich","ror":"https://ror.org/02nv7yv05","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I171892758"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gabriele Cavallaro","raw_affiliation_strings":["J\u00fclich Supercomputing Centre, Forschungszentrum, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J\u00fclich Supercomputing Centre, Forschungszentrum, Germany","institution_ids":["https://openalex.org/I171892758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085870953","display_name":"Jenia Jitsev","orcid":"https://orcid.org/0000-0002-1221-7851"},"institutions":[{"id":"https://openalex.org/I171892758","display_name":"Forschungszentrum J\u00fclich","ror":"https://ror.org/02nv7yv05","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I171892758"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jenia Jitsev","raw_affiliation_strings":["J\u00fclich Supercomputing Centre, Forschungszentrum, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J\u00fclich Supercomputing Centre, Forschungszentrum, Germany","institution_ids":["https://openalex.org/I171892758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2726,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.83054774,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9993000030517578,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.8479019403457642},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.777524471282959},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6490691900253296},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5414076447486877},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5127862095832825},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.49516573548316956},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.45285043120384216},{"id":"https://openalex.org/keywords/supercomputer","display_name":"Supercomputer","score":0.41965538263320923},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3538162112236023},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.33996647596359253},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.32682889699935913},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.17221292853355408},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.114987313747406}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8479019403457642},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.777524471282959},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6490691900253296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5414076447486877},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5127862095832825},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.49516573548316956},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.45285043120384216},{"id":"https://openalex.org/C83283714","wikidata":"https://www.wikidata.org/wiki/Q121117","display_name":"Supercomputer","level":2,"score":0.41965538263320923},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3538162112236023},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.33996647596359253},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.32682889699935913},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.17221292853355408},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.114987313747406},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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":2,"locations":[{"id":"doi:10.1109/igarss39084.2020.9323734","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323734","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:publications.rwth-aachen.de:825146","is_oa":false,"landing_page_url":"https://publications.rwth-aachen.de/record/825146","pdf_url":null,"source":{"id":"https://openalex.org/S4306401033","display_name":"RWTH Publications (RWTH Aachen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887968799","host_organization_name":"RWTH Aachen University","host_organization_lineage":["https://openalex.org/I887968799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 IEEE International Geoscience & Remote Sensing Symposium : proceedings : September 26-October 2, 2020, virtual / sponsored by the Institute of Electrical and Electronics Engineers, Geoscience and Remote Sensing Society<br/>2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020, online, 2020-09-26 - 2020-10-02","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1095062678","display_name":null,"funder_award_id":"604102","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2056435747","https://openalex.org/W2057332538","https://openalex.org/W2171845746","https://openalex.org/W2528170672","https://openalex.org/W2622263826","https://openalex.org/W2786720420","https://openalex.org/W2787998955","https://openalex.org/W2794252992","https://openalex.org/W2804078698","https://openalex.org/W2911583375","https://openalex.org/W2940726923","https://openalex.org/W2962723135","https://openalex.org/W2964164961","https://openalex.org/W2964213118","https://openalex.org/W4301239768","https://openalex.org/W6685078114"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2027972911","https://openalex.org/W2013643406","https://openalex.org/W2157978810","https://openalex.org/W2597809628","https://openalex.org/W2790610275"],"abstract_inverted_index":{"This":[0],"work":[1],"proposes":[2],"a":[3],"novel":[4],"distributed":[5],"deep":[6,44],"learning":[7,27,45,96],"model":[8,46,70],"for":[9],"Remote":[10],"Sensing":[11],"(RS)":[12],"images":[13],"super-resolution.":[14],"High":[15],"Performance":[16],"Computing":[17],"(HPC)":[18],"systems":[19],"with":[20],"GPUs":[21],"are":[22],"used":[23],"to":[24,32,78,93],"accelerate":[25],"the":[26,29,66,69,81],"of":[28,39,68],"unknown":[30],"low":[31],"high":[33],"resolution":[34],"mapping":[35],"from":[36],"large":[37],"volumes":[38],"Sentinel-2":[40],"data.":[41],"The":[42,55],"proposed":[43],"is":[47,76,90],"based":[48],"on":[49],"self-attention":[50],"mechanism":[51],"and":[52],"residual":[53],"learning.":[54],"results":[56],"demonstrate":[57],"that":[58],"state-of-the-art":[59],"performance":[60,86,100],"can":[61],"be":[62],"achieved":[63],"by":[64],"keeping":[65,99],"size":[67],"relatively":[71],"small.":[72],"Synchronous":[73],"data":[74],"parallelism":[75],"applied":[77],"scale":[79],"up":[80,95],"training":[82,89],"process":[83],"without":[84],"severe":[85],"loss.":[87],"Distributed":[88],"thus":[91],"shown":[92],"speed":[94],"substantially":[97],"while":[98],"intact.":[101]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}