乐胖代购免代理版

{"id":"https://openalex.org/W3048727046","doi":"https://doi.org/10.1117/1.jei.29.4.043020","title":"Multinoise-type blind denoising using a single uniform deep convolutional neural network","display_name":"Multinoise-type blind denoising using a single uniform deep convolutional neural network","publication_year":2020,"publication_date":"2020-08-10","ids":{"openalex":"https://openalex.org/W3048727046","doi":"https://doi.org/10.1117/1.jei.29.4.043020","mag":"3048727046"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.jei.29.4.043020","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5081897358","display_name":"Caiyang Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"funder","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caiyang Xie","raw_affiliation_strings":["Zhejiang University, Institute of Advanced Digital Technologies and Instrument, Hangzhou"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Institute of Advanced Digital Technologies and Instrument, Hangzhou","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008526350","display_name":"Yaowu Chen","orcid":"https://orcid.org/0000-0002-6037-0631"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"funder","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaowu Chen","raw_affiliation_strings":["Zhejiang University, Institute of Advanced Digital Technologies and Instrument, Hangzhou"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Institute of Advanced Digital Technologies and Instrument, Hangzhou","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028024624","display_name":"Rongxin Jiang","orcid":"https://orcid.org/0000-0001-7901-3047"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"funder","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongxin Jiang","raw_affiliation_strings":["Zhejiang University, Institute of Advanced Digital Technologies and Instrument, Hangzhou"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Institute of Advanced Digital Technologies and Instrument, Hangzhou","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100681842","display_name":"Shengyu Li","orcid":"https://orcid.org/0000-0002-4907-4014"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"funder","lineage":["https://openalex.org/I76130692"]},{"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":"Shengyu Li","raw_affiliation_strings":["Alibaba Group (China)","Zhejiang University, Institute of Advanced Digital Technologies and Instrument, Hangzhou"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Institute of Advanced Digital Technologies and Instrument, Hangzhou","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Alibaba Group (China)","institution_ids":["https://openalex.org/I45928872"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":60},"biblio":{"volume":"29","issue":"04","first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9989,"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":0.9989,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9749,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9747,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/video-denoising","display_name":"Video denoising","score":0.48860127},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian Noise","score":0.48509538},{"id":"https://openalex.org/keywords/non-local-means","display_name":"Non-Local Means","score":0.4244036},{"id":"https://openalex.org/keywords/salt-and-pepper-noise","display_name":"Salt-and-pepper noise","score":0.42213517}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.79338795},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.72815573},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6888326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.68505406},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6182946},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.55451995},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.48860127},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.48509538},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43840808},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4330093},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.42759347},{"id":"https://openalex.org/C101453961","wikidata":"https://www.wikidata.org/wiki/Q7048948","display_name":"Non-local means","level":4,"score":0.4244036},{"id":"https://openalex.org/C113660513","wikidata":"https://www.wikidata.org/wiki/Q849379","display_name":"Salt-and-pepper noise","level":5,"score":0.42213517},{"id":"https://openalex.org/C55352655","wikidata":"https://www.wikidata.org/wiki/Q304247","display_name":"Median filter","level":4,"score":0.28922033},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27625442},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.23729569},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18579465},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.14656663},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.0},{"id":"https://openalex.org/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.jei.29.4.043020","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"31627802"}],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W972036175","https://openalex.org/W2960360058","https://openalex.org/W2811019791","https://openalex.org/W2364780020","https://openalex.org/W2240596953","https://openalex.org/W2123496732","https://openalex.org/W2120405331","https://openalex.org/W2116036791","https://openalex.org/W2090859501","https://openalex.org/W2027616686"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1],"neural":[2],"networks":[3],"(CNNs)":[4],"have":[5],"achieved":[6],"considerable":[7],"success":[8],"with":[9],"image":[10,90],"denoising.":[11],"However,":[12],"they":[13],"still":[14],"lack":[15],"consistent":[16],"performance":[17,160],"across":[18],"different":[19],"noise":[20,26],"types":[21],"and":[22,34,76,91,119,142,145,161],"levels.":[23],"We":[24,36],"extend":[25],"scenarios":[27],"to":[28,72,94,154],"four":[29],"categories:":[30],"Gaussian,":[31],"random-impulse,":[32],"salt-and-pepper,":[33],"Poisson.":[35],"also":[37],"propose":[38],"a":[39,52,66,112],"multinoise-type":[40],"blind":[41,48],"denoising":[42,49,97,109,143,159],"network":[43,58],"(MBDNet)":[44],"that":[45,147],"solves":[46],"the":[47,88,95,107,116,122,126,137,140],"task":[50],"using":[51],"uniform":[53],"deep":[54,128],"CNN":[55,68],"architecture.":[56],"The":[57],"can":[59],"be":[60],"divided":[61],"into":[62],"two":[63],"stages":[64],"where":[65],"concise":[67],"is":[69,103,149],"first":[70],"used":[71],"estimate":[73],"auxiliary":[74],"noise-type":[75],"noise-level":[77],"information.":[78],"Estimation":[79],"results":[80],"are":[81,92],"then":[82],"integrated":[83],"as":[84,152],"additional":[85],"channels":[86],"of":[87,125,139],"noisy":[89,134],"fed":[93],"subsequent":[96],"stage.":[98],"A":[99],"unique":[100],"two-branch":[101],"structure":[102],"further":[104],"adopted":[105],"in":[106,157],"residual":[108],"CNN,":[110],"wherein":[111],"shallow":[113],"branch":[114],"predicts":[115],"filter-flow":[117],"mask":[118],"adaptively":[120],"adjusts":[121],"feature":[123],"extraction":[124],"parallel":[127],"branch.":[129],"Extensive":[130],"experiments":[131],"on":[132],"synthetic":[133],"images":[135],"validate":[136],"effectiveness":[138],"noise-estimation":[141],"subnetworks":[144],"show":[146],"MBDNet":[148],"highly":[150],"competitive":[151],"compared":[153],"state-of-the-art":[155],"methods":[156],"both":[158],"model":[162],"runtime.":[163]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3048727046","counts_by_year":[],"updated_date":"2025-01-26T22:00:35.836150","created_date":"2020-08-18"}