{"id":"https://openalex.org/W3102348318","doi":"https://doi.org/10.1109/tgrs.2020.3036065","title":"Denoising the Optical Fiber Seismic Data by Using Convolutional Adversarial Network Based on Loss Balance","display_name":"Denoising the Optical Fiber Seismic Data by Using Convolutional Adversarial Network Based on Loss Balance","publication_year":2020,"publication_date":"2020-11-16","ids":{"openalex":"https://openalex.org/W3102348318","doi":"https://doi.org/10.1109/tgrs.2020.3036065","mag":"3102348318"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.3036065","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3036065","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-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/A5087029680","display_name":"Xintong Dong","orcid":"https://orcid.org/0000-0001-6657-6289"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xintong Dong","raw_affiliation_strings":["Department of Information, College of Communication Engineering, Jilin University, Changchun, China"],"affiliations":[{"raw_affiliation_string":"Department of Information, College of Communication Engineering, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100621538","display_name":"Yue Li","orcid":"https://orcid.org/0000-0001-5482-6244"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Li","raw_affiliation_strings":["Department of Information, College of Communication Engineering, Jilin University, Changchun, China"],"affiliations":[{"raw_affiliation_string":"Department of Information, College of Communication Engineering, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087029680"],"corresponding_institution_ids":["https://openalex.org/I194450716"],"apc_list":null,"apc_paid":null,"fwci":9.7517,"has_fulltext":false,"cited_by_count":97,"citation_normalized_percentile":{"value":0.99149026,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"59","issue":"12","first_page":"10544","last_page":"10554"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11757","display_name":"Seismic Waves and Analysis","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11757","display_name":"Seismic Waves and Analysis","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"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/T10205","display_name":"Advanced Fiber Optic Sensors","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11569","display_name":"Optical Coherence Tomography Applications","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.7149606943130493},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6684931516647339},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.6386393904685974},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.47907501459121704},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4543853998184204},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4401693642139435},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4385569393634796},{"id":"https://openalex.org/keywords/coupling-loss","display_name":"Coupling loss","score":0.43604597449302673},{"id":"https://openalex.org/keywords/data-loss","display_name":"Data loss","score":0.4293571710586548},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3422447443008423},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3359833061695099},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.25857770442962646},{"id":"https://openalex.org/keywords/optical-fiber","display_name":"Optical fiber","score":0.1823999285697937},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11054876446723938}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7149606943130493},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6684931516647339},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6386393904685974},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.47907501459121704},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4543853998184204},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4401693642139435},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4385569393634796},{"id":"https://openalex.org/C21792228","wikidata":"https://www.wikidata.org/wiki/Q5178039","display_name":"Coupling loss","level":3,"score":0.43604597449302673},{"id":"https://openalex.org/C193519340","wikidata":"https://www.wikidata.org/wiki/Q891179","display_name":"Data loss","level":2,"score":0.4293571710586548},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3422447443008423},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3359833061695099},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.25857770442962646},{"id":"https://openalex.org/C194232370","wikidata":"https://www.wikidata.org/wiki/Q162","display_name":"Optical fiber","level":2,"score":0.1823999285697937},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11054876446723938},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2020.3036065","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3036065","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G5755307398","display_name":null,"funder_award_id":"41974143","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6212813170","display_name":null,"funder_award_id":"41730422","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1900713400","https://openalex.org/W1967469577","https://openalex.org/W2028513246","https://openalex.org/W2033875610","https://openalex.org/W2046816840","https://openalex.org/W2078546002","https://openalex.org/W2108473160","https://openalex.org/W2129949570","https://openalex.org/W2132454757","https://openalex.org/W2150117578","https://openalex.org/W2164000238","https://openalex.org/W2170860899","https://openalex.org/W2186316592","https://openalex.org/W2317974577","https://openalex.org/W2416739439","https://openalex.org/W2510593588","https://openalex.org/W2518468762","https://openalex.org/W2520164769","https://openalex.org/W2617128058","https://openalex.org/W2730411900","https://openalex.org/W2781854221","https://openalex.org/W2791941428","https://openalex.org/W2805898668","https://openalex.org/W2898524492","https://openalex.org/W2899651173","https://openalex.org/W2901354392","https://openalex.org/W2904236774","https://openalex.org/W2907551576","https://openalex.org/W2915004230","https://openalex.org/W2923341372","https://openalex.org/W2940419603","https://openalex.org/W2947066362","https://openalex.org/W2947589767","https://openalex.org/W2949939119","https://openalex.org/W2951689089","https://openalex.org/W2952480641","https://openalex.org/W2958903376","https://openalex.org/W2970679026","https://openalex.org/W2970694612","https://openalex.org/W2970715218","https://openalex.org/W2972043148","https://openalex.org/W2982704408","https://openalex.org/W2983431682","https://openalex.org/W2984306354","https://openalex.org/W2984915066","https://openalex.org/W2996149614","https://openalex.org/W3003534375","https://openalex.org/W3013707453","https://openalex.org/W3022413839","https://openalex.org/W3099006605","https://openalex.org/W3102755745","https://openalex.org/W4242059867","https://openalex.org/W4320013936","https://openalex.org/W6726381175","https://openalex.org/W6776641088"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W4380714744","https://openalex.org/W2387995142","https://openalex.org/W4319453655","https://openalex.org/W2057775761","https://openalex.org/W2964074194","https://openalex.org/W2066597623","https://openalex.org/W4385545089"],"abstract_inverted_index":{"Distributed":[0],"optical":[1,24],"fiber":[2],"acoustic":[3],"sensing":[4],"(DAS)":[5],"is":[6,53,75,138,185],"a":[7,76,103,123,172],"new":[8,77],"and":[9,26,33,64,95,119,149,155,163,182,194,219],"rapid-developing":[10],"detection":[11],"technology":[12],"in":[13,130],"seismic":[14,37,85,93,225],"exploration.":[15],"Unfortunately,":[16],"due":[17],"to":[18,55,125,199],"the":[19,27,36,68,72,89,97,111,120,127,134,150,156,160,166,177,189,201,216,221,231,236],"weak":[20,238],"energy":[21],"of":[22,79,91,114,122,136,168,180,204,215,223],"scattered":[23],"signals":[25,233,240],"inferior":[28,73],"coupling":[29,74],"between":[30,153],"DAS":[31,41,92,98,217,224],"cable":[32],"receiving":[34],"interface,":[35],"data":[38,94],"received":[39],"by":[40,45,71,187,242],"are":[42,197],"often":[43],"characterized":[44],"low":[46,51],"signal-to-noise":[47],"ratio":[48,179],"(SNR);":[49],"this":[50],"SNR":[52,90,222],"likely":[54],"affect":[56],"some":[57],"subsequent":[58],"analysis,":[59],"such":[60],"as":[61],"inversion,":[62],"imaging,":[63],"interpretation.":[65],"In":[66,132],"addition,":[67],"noise":[69,80,99,218],"caused":[70],"kind":[78],"not":[81],"presented":[82],"on":[83,110],"conventional":[84],"data.":[86],"To":[87,158],"enhance":[88,220],"suppress":[96,213],"effectively,":[100],"we":[101,170],"propose":[102],"convolutional":[104],"adversarial":[105,116,151,183],"denoising":[106,190,202],"network":[107,117],"(CADN)":[108],"based":[109],"basic":[112],"strategy":[113],"generative":[115],"(GAN)":[118],"usage":[121],"denoiser":[124,137],"replace":[126],"original":[128],"generator":[129],"GAN.":[131],"CADN,":[133],"performance":[135,203],"significantly":[139],"strengthened":[140],"via":[141],"its":[142],"own":[143],"mean":[144],"square":[145],"error":[146],"(MSE)":[147],"loss":[148,152,174],"it":[154,228],"discriminator.":[157],"balance":[159],"two":[161],"losses":[162,184],"thus":[164],"ensure":[165],"optimization":[167],"denoiser,":[169],"construct":[171],"novel":[173],"function,":[175],"where":[176],"optimal":[178],"MSE":[181],"determined":[186],"quantifying":[188],"performance.":[191],"Both":[192],"real":[193],"synthetic":[195],"examples":[196],"included":[198],"testify":[200],"CADN.":[205],"Experimental":[206],"results":[207],"have":[208],"demonstrated":[209],"that":[210],"CADN":[211],"can":[212,229],"most":[214],"data;":[226],"also,":[227],"recover":[230],"effective":[232,239],"completely,":[234],"even":[235],"extremely":[237],"reflected":[241],"deep":[243],"layers.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}