{"id":"https://openalex.org/W3110214053","doi":"https://doi.org/10.1109/cisp-bmei51763.2020.9263524","title":"A Deep Meta-Learning Neural Network for Single Image Rain Removal","display_name":"A Deep Meta-Learning Neural Network for Single Image Rain Removal","publication_year":2020,"publication_date":"2020-10-17","ids":{"openalex":"https://openalex.org/W3110214053","doi":"https://doi.org/10.1109/cisp-bmei51763.2020.9263524","mag":"3110214053"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei51763.2020.9263524","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei51763.2020.9263524","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5024636195","display_name":"Yihong Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123940","display_name":"Ministry of Education","ror":"https://ror.org/02xv42m49","country_code":"PT","type":"government","lineage":["https://openalex.org/I4210117458","https://openalex.org/I4210123940"]},{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN","PT"],"is_corresponding":true,"raw_author_name":"Yihong Lu","raw_affiliation_strings":["Fujian Normal University,Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education,China","Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, China"],"affiliations":[{"raw_affiliation_string":"Fujian Normal University,Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education,China","institution_ids":["https://openalex.org/I111753288","https://openalex.org/I4210123940"]},{"raw_affiliation_string":"Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100507873","display_name":"Jianyong Cai","orcid":"https://orcid.org/0009-0000-3804-9932"},"institutions":[{"id":"https://openalex.org/I4210123940","display_name":"Ministry of Education","ror":"https://ror.org/02xv42m49","country_code":"PT","type":"government","lineage":["https://openalex.org/I4210117458","https://openalex.org/I4210123940"]},{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN","PT"],"is_corresponding":false,"raw_author_name":"Jianyong Cai","raw_affiliation_strings":["Fujian Normal University,Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education,China","Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, China"],"affiliations":[{"raw_affiliation_string":"Fujian Normal University,Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education,China","institution_ids":["https://openalex.org/I111753288","https://openalex.org/I4210123940"]},{"raw_affiliation_string":"Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101567437","display_name":"Hua Zheng","orcid":"https://orcid.org/0000-0003-2090-1239"},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua Zheng","raw_affiliation_strings":["Fujian Normal University,College of Photonic and Electronic Engineering,China","College of Photonic and Electronic Engineering, Fujian Normal University, China"],"affiliations":[{"raw_affiliation_string":"Fujian Normal University,College of Photonic and Electronic Engineering,China","institution_ids":["https://openalex.org/I111753288"]},{"raw_affiliation_string":"College of Photonic and Electronic Engineering, Fujian Normal University, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079217524","display_name":"Yuanqiang Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanqiang Zeng","raw_affiliation_strings":["Fujian Normal University,College of Photonic and Electronic Engineering,China","College of Photonic and Electronic Engineering, Fujian Normal University, China"],"affiliations":[{"raw_affiliation_string":"Fujian Normal University,College of Photonic and Electronic Engineering,China","institution_ids":["https://openalex.org/I111753288"]},{"raw_affiliation_string":"College of Photonic and Electronic Engineering, Fujian Normal University, China","institution_ids":["https://openalex.org/I111753288"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024636195"],"corresponding_institution_ids":["https://openalex.org/I111753288","https://openalex.org/I4210123940"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.14285474,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"231","last_page":"237"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement 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/T11019","display_name":"Image Enhancement 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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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":0.9991000294685364,"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/computer-science","display_name":"Computer science","score":0.7897630333900452},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6940692067146301},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.5932873487472534},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5876960754394531},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5690770745277405},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5589675307273865},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5298599600791931},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5088017582893372},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5046948194503784},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49980926513671875},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4907158613204956},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42396196722984314},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41898593306541443},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4185160994529724},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10549366474151611},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09596788883209229},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.05676513910293579}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7897630333900452},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6940692067146301},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.5932873487472534},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5876960754394531},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5690770745277405},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5589675307273865},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5298599600791931},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5088017582893372},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5046948194503784},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49980926513671875},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4907158613204956},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42396196722984314},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41898593306541443},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4185160994529724},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10549366474151611},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09596788883209229},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.05676513910293579},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei51763.2020.9263524","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei51763.2020.9263524","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1572507715","https://openalex.org/W1598377843","https://openalex.org/W1976056157","https://openalex.org/W1986266272","https://openalex.org/W1992687477","https://openalex.org/W2005876512","https://openalex.org/W2017416107","https://openalex.org/W2054604489","https://openalex.org/W2090378746","https://openalex.org/W2114770744","https://openalex.org/W2119535410","https://openalex.org/W2121396509","https://openalex.org/W2122596619","https://openalex.org/W2125188192","https://openalex.org/W2133665775","https://openalex.org/W2150385401","https://openalex.org/W2154621477","https://openalex.org/W2157674331","https://openalex.org/W2163146621","https://openalex.org/W2177195834","https://openalex.org/W2206123561","https://openalex.org/W2209874411","https://openalex.org/W2432717477","https://openalex.org/W2466666260","https://openalex.org/W2508457857","https://openalex.org/W2509784253","https://openalex.org/W2519153507","https://openalex.org/W2604763608","https://openalex.org/W2611035488","https://openalex.org/W2740982616","https://openalex.org/W2777170053","https://openalex.org/W2778532031","https://openalex.org/W2790425328","https://openalex.org/W2791592182","https://openalex.org/W2884068670","https://openalex.org/W2913360047","https://openalex.org/W2963341924","https://openalex.org/W2963775850","https://openalex.org/W2964023155","https://openalex.org/W2964121744","https://openalex.org/W2964212750","https://openalex.org/W4285719527","https://openalex.org/W6631190155","https://openalex.org/W6635862820","https://openalex.org/W6682639118","https://openalex.org/W6726404322","https://openalex.org/W6736057607"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W4375867731","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W2239445980","https://openalex.org/W2080152487","https://openalex.org/W3083152911","https://openalex.org/W2061571973"],"abstract_inverted_index":{"Due":[0],"to":[1,42,60,63,77,91,102,130,167],"various":[2,47,135],"interference":[3,171],"factors,":[4,173],"image":[5,19,170,177],"degradation":[6],"seriously":[7],"retards":[8],"the":[9,26,50,65,79,104,108,111,144],"precision":[10],"and":[11,16,110,158,180],"efficiency":[12],"of":[13,28,67,107,114],"target":[14],"tracking":[15],"recognition.":[17],"Consequently,":[18],"restoration":[20],"becomes":[21],"a":[22,34],"significant":[23],"issue":[24],"in":[25,46,75,147],"field":[27],"computer":[29],"vision.":[30],"In":[31],"this":[32,148],"paper,":[33],"novel":[35],"de-rain":[36],"network,":[37,109],"called":[38],"Meta-DerainNet":[39],"was":[40,116,127],"proposed":[41,146],"remove":[43,131],"rain":[44,69,83,132],"streaks":[45,70,133],"conditions.":[48,136],"With":[49],"strongly":[51],"generation":[52],"ability,":[53],"Model-Agnostic":[54],"Meta-Learning":[55],"(MAML)":[56],"has":[57],"been":[58],"proven":[59],"be":[61,92,165],"able":[62],"accomplish":[64],"task":[66],"removing":[68],"from":[71],"single":[72],"image.":[73],"However,":[74],"order":[76],"combine":[78],"MAML":[80,115],"algorithm":[81],"with":[82,96],"removal":[84,172],"tasks,":[85],"there":[86],"are":[87],"many":[88],"parts":[89],"need":[90],"improved.":[93],"The":[94,124],"datasets":[95],"specific":[97],"sample":[98],"methods":[99,155],"were":[100],"designed":[101],"train":[103],"generalization":[105],"ability":[106],"network":[112,126],"structured":[113],"improved":[117],"for":[118],"more":[119],"efficiently":[120],"extract":[121],"feature":[122],"map.":[123],"modified":[125],"successfully":[128],"applied":[129,166],"under":[134],"Experimental":[137],"results":[138],"on":[139,156],"real-world":[140],"data":[141],"show":[142],"that":[143],"method":[145,162],"paper":[149],"performs":[150],"better":[151],"than":[152],"other":[153,169,181],"advanced":[154],"PSNR":[157],"SSIM.":[159],"Furthermore,":[160],"our":[161],"can":[163],"also":[164],"process":[168],"such":[174],"as":[175],"medical":[176],"recognition,":[178],"self-driving":[179],"fields.":[182]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}