{"id":"https://openalex.org/W4200348065","doi":"https://doi.org/10.3390/rs14010024","title":"Towards a More Realistic and Detailed Deep-Learning-Based Radar Echo Extrapolation Method","display_name":"Towards a More Realistic and Detailed Deep-Learning-Based Radar Echo Extrapolation Method","publication_year":2021,"publication_date":"2021-12-22","ids":{"openalex":"https://openalex.org/W4200348065","doi":"https://doi.org/10.3390/rs14010024"},"language":"en","primary_location":{"id":"doi:10.3390/rs14010024","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14010024","pdf_url":"https://www.mdpi.com/2072-4292/14/1/24/pdf?version=1640221759","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/2072-4292/14/1/24/pdf?version=1640221759","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006947125","display_name":"Yuan Hu","orcid":"https://orcid.org/0000-0003-1256-7023"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuan Hu","raw_affiliation_strings":["DAMO Academy, Alibaba Group, Beijing 100102, China"],"affiliations":[{"raw_affiliation_string":"DAMO Academy, Alibaba Group, Beijing 100102, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333564","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0003-2760-1124"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["DAMO Academy, Alibaba Group, Beijing 100102, China"],"affiliations":[{"raw_affiliation_string":"DAMO Academy, Alibaba Group, Beijing 100102, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100332272","display_name":"Zhibin Wang","orcid":"https://orcid.org/0000-0001-7502-2181"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibin Wang","raw_affiliation_strings":["DAMO Academy, Alibaba Group, Beijing 100102, China"],"affiliations":[{"raw_affiliation_string":"DAMO Academy, Alibaba Group, Beijing 100102, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076349830","display_name":"Xiang Pan","orcid":"https://orcid.org/0000-0003-3890-6599"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]},{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Pan","raw_affiliation_strings":["DAMO Academy, Alibaba Group, Beijing 100102, China","Key Laboratory of Mesoscale Severe Weather/MOE, School of Atmospheric Sciences, Nanjing University, Nanjing 210033, China"],"affiliations":[{"raw_affiliation_string":"DAMO Academy, Alibaba Group, Beijing 100102, China","institution_ids":["https://openalex.org/I45928872"]},{"raw_affiliation_string":"Key Laboratory of Mesoscale Severe Weather/MOE, School of Atmospheric Sciences, Nanjing University, Nanjing 210033, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100348522","display_name":"Hao Li","orcid":"https://orcid.org/0000-0001-9305-8524"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Li","raw_affiliation_strings":["DAMO Academy, Alibaba Group, Beijing 100102, China"],"affiliations":[{"raw_affiliation_string":"DAMO Academy, Alibaba Group, Beijing 100102, China","institution_ids":["https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5006947125"],"corresponding_institution_ids":["https://openalex.org/I45928872"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":2.1135,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.89424837,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"14","issue":"1","first_page":"24","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9983000159263611,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9983000159263611,"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/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9976999759674072,"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":0.7987909317016602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6797044277191162},{"id":"https://openalex.org/keywords/extrapolation","display_name":"Extrapolation","score":0.6518977880477905},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5941842794418335},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5596329569816589},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5308438539505005},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.46861037611961365},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4528133273124695},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.4509276747703552},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3672545552253723},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35895347595214844},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32116323709487915},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20869264006614685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11469051241874695}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7987909317016602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6797044277191162},{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.6518977880477905},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5941842794418335},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5596329569816589},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5308438539505005},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.46861037611961365},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4528133273124695},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.4509276747703552},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3672545552253723},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35895347595214844},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32116323709487915},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20869264006614685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11469051241874695},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14010024","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14010024","pdf_url":"https://www.mdpi.com/2072-4292/14/1/24/pdf?version=1640221759","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:36e2c36370ae49038d79ad68df4281aa","is_oa":true,"landing_page_url":"https://doaj.org/article/36e2c36370ae49038d79ad68df4281aa","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 1, p 24 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/1/24/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14010024","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 1; Pages: 24","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14010024","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14010024","pdf_url":"https://www.mdpi.com/2072-4292/14/1/24/pdf?version=1640221759","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":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4200348065.pdf","grobid_xml":"https://content.openalex.org/works/W4200348065.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1580389772","https://openalex.org/W1901129140","https://openalex.org/W2016184960","https://openalex.org/W2024414272","https://openalex.org/W2042172159","https://openalex.org/W2106822551","https://openalex.org/W2118877769","https://openalex.org/W2133665775","https://openalex.org/W2141983208","https://openalex.org/W2163605009","https://openalex.org/W2174781512","https://openalex.org/W2331128040","https://openalex.org/W2475287302","https://openalex.org/W2612034718","https://openalex.org/W2768975186","https://openalex.org/W2787614951","https://openalex.org/W2807451848","https://openalex.org/W2886787375","https://openalex.org/W2913323966","https://openalex.org/W2943446701","https://openalex.org/W2962785568","https://openalex.org/W2963289467","https://openalex.org/W2965679379","https://openalex.org/W2967033144","https://openalex.org/W2972792628","https://openalex.org/W3009216045","https://openalex.org/W3016496098","https://openalex.org/W3047250172","https://openalex.org/W3048374358","https://openalex.org/W3104861085","https://openalex.org/W3110422536","https://openalex.org/W3173275980","https://openalex.org/W3184447318","https://openalex.org/W3186404120","https://openalex.org/W3202525453","https://openalex.org/W3207011416","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W1968270095","https://openalex.org/W2220129715","https://openalex.org/W4296478327","https://openalex.org/W2042397106","https://openalex.org/W4361730764","https://openalex.org/W1965029248","https://openalex.org/W2333625343","https://openalex.org/W1960072520","https://openalex.org/W2154140103","https://openalex.org/W2020512427"],"abstract_inverted_index":{"Deep-learning-based":[0],"radar":[1,53,126,224],"echo":[2,54],"extrapolation":[3,55],"methods":[4,56,231],"have":[5,30],"achieved":[6],"remarkable":[7],"progress":[8],"in":[9,33],"the":[10,36,89,98,116,120,138,144,154,162,209,214],"precipitation":[11],"nowcasting":[12],"field.":[13],"However,":[14],"they":[15],"suffer":[16],"from":[17,97,141,165],"a":[18,67,74,107,133,150,166,176,187],"common":[19],"notorious":[20],"problem\u2014they":[21],"tend":[22],"to":[23,50,57,77,113,128,136,143,160,178,185,219,236,242],"produce":[24,220],"blurry":[25],"predictions.":[26],"Although":[27],"some":[28],"efforts":[29],"been":[31],"made":[32],"recent":[34],"years,":[35],"blurring":[37],"problem":[38],"is":[39,111],"still":[40],"under-addressed.":[41],"In":[42,105],"this":[43],"work,":[44],"we":[45,65,147],"propose":[46,66],"three":[47],"effective":[48],"strategies":[49],"assist":[51],"deep-learning-based":[52,238],"achieve":[58,186],"more":[59,222,244],"realistic":[60,223],"and":[61,73,83,94,101,201,204],"detailed":[62,121,245],"prediction.":[63],"Specifically,":[64],"spatial":[68,82,99],"generative":[69],"adversarial":[70],"network":[71],"(GAN)":[72],"spectrum":[75,84],"GAN":[76],"improve":[78],"image":[79,191],"fidelity.":[80],"The":[81,169],"GANs":[85],"aim":[86],"at":[87],"penalizing":[88],"distribution":[90],"discrepancy":[91],"between":[92],"generated":[93],"real":[95],"images":[96,225],"domain":[100],"spectral":[102,156],"domain,":[103],"respectively.":[104],"addition,":[106],"masked":[108],"style":[109],"loss":[110],"devised":[112],"further":[114],"enhance":[115],"details":[117],"by":[118],"transferring":[119,142],"texture":[122],"of":[123,190],"ground":[124],"truth":[125],"sequences":[127],"extrapolated":[129],"ones.":[130],"We":[131,193],"apply":[132],"foreground":[134],"mask":[135],"prevent":[137],"background":[139],"noise":[140],"outputs.":[145],"Moreover,":[146],"also":[148],"design":[149],"new":[151],"metric":[152,171],"termed":[153],"power":[155],"density":[157],"score":[158],"(PSDS)":[159],"quantify":[161],"perceptual":[163],"quality":[164],"frequency":[167],"perspective.":[168],"PSDS":[170],"can":[172,232],"be":[173,233],"applied":[174,235],"as":[175],"complement":[177],"other":[179],"visual":[180],"evaluation":[181],"metrics":[182],"(e.g.,":[183],"LPIPS)":[184],"comprehensive":[188,205],"measurement":[189],"sharpness.":[192],"test":[194],"our":[195,230],"approaches":[196,216],"with":[197],"both":[198],"ConvLSTM":[199],"baseline":[200],"U-Net":[202],"baseline,":[203],"ablation":[206],"experiments":[207],"on":[208],"SEVIR":[210],"dataset":[211],"show":[212],"that":[213],"proposed":[215],"are":[217],"able":[218],"much":[221],"than":[226],"baselines.":[227],"Most":[228],"notably,":[229],"readily":[234],"any":[237],"spatiotemporal":[239],"forecasting":[240],"models":[241],"acquire":[243],"results.":[246]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
