iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.openalex.org/works/doi:10.1109/TGRS.2022.3158389
{"id":"https://openalex.org/W4226266787","doi":"https://doi.org/10.1109/tgrs.2022.3158389","title":"Unsupervised Erratic Seismic Noise Attenuation With Robust Deep Convolutional Autoencoders","display_name":"Unsupervised Erratic Seismic Noise Attenuation With Robust Deep Convolutional Autoencoders","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4226266787","doi":"https://doi.org/10.1109/tgrs.2022.3158389"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3158389","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":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/A5070316685","display_name":"Feng Qian","orcid":"https://orcid.org/0000-0002-4761-3598"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Qian","raw_affiliation_strings":["Center for Information Geoscience and the School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Center for Information Geoscience and the School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068541324","display_name":"Wei Guo","orcid":"https://orcid.org/0000-0001-8360-179X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Guo","raw_affiliation_strings":["Center for Information Geoscience and the School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Center for Information Geoscience and the School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038051263","display_name":"Zhangbo Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhangbo Liu","raw_affiliation_strings":["Center for Information Geoscience and the School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Center for Information Geoscience and the School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074138884","display_name":"Hongtao Yu","orcid":"https://orcid.org/0000-0002-8596-5527"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongtao Yu","raw_affiliation_strings":["Center for Information Geoscience and the School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Center for Information Geoscience and the School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058079274","display_name":"Gulan Zhang","orcid":"https://orcid.org/0000-0002-7603-4966"},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gulan Zhang","raw_affiliation_strings":["School of Geoscience and Technology, Southwest Petroleum University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Geoscience and Technology, Southwest Petroleum University, Chengdu, China","institution_ids":["https://openalex.org/I165745306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058780083","display_name":"Guangmin Hu","orcid":"https://orcid.org/0000-0002-4694-9145"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangmin Hu","raw_affiliation_strings":["Center for Information Geoscience and the School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Center for Information Geoscience and the School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.097,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.999901,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Waveform Inversion in Geophysics","score":0.9999,"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/T10271","display_name":"Seismic Waveform Inversion in Geophysics","score":0.9999,"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/T10688","display_name":"Image Denoising Techniques and Algorithms","score":0.9964,"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/T11757","display_name":"High-Resolution Seismic Noise Tomography","score":0.9964,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/distributed-acoustic-sensing","display_name":"Distributed Acoustic Sensing","score":0.573923},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image Denoising","score":0.570624},{"id":"https://openalex.org/keywords/seismic-noise","display_name":"Seismic Noise","score":0.563359},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5368659},{"id":"https://openalex.org/keywords/seismic-data-processing","display_name":"Seismic Data Processing","score":0.5299},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian Noise","score":0.519467},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.41225654}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6453716},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.59946406},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5696864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.54729676},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5368659},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5098678},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.50250006},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4977124},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.46203047},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44722217},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.41235983},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.41225654},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38685393},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24635923},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19426343},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11980218}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3158389","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":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":"41874155"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"41874168"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"42130812"}],"datasets":[],"versions":[],"referenced_works_count":67,"referenced_works":["https://openalex.org/W1853998970","https://openalex.org/W1922005389","https://openalex.org/W1941471881","https://openalex.org/W1970840033","https://openalex.org/W1973540739","https://openalex.org/W1990309165","https://openalex.org/W2010535094","https://openalex.org/W2021734622","https://openalex.org/W2054834816","https://openalex.org/W2080818349","https://openalex.org/W2086288874","https://openalex.org/W2122752532","https://openalex.org/W2132454757","https://openalex.org/W2145962650","https://openalex.org/W2182747765","https://openalex.org/W2271808722","https://openalex.org/W2282024151","https://openalex.org/W2294674895","https://openalex.org/W2318387983","https://openalex.org/W2328740995","https://openalex.org/W2403089413","https://openalex.org/W2463531433","https://openalex.org/W2593317637","https://openalex.org/W2606536852","https://openalex.org/W2612643985","https://openalex.org/W2614683497","https://openalex.org/W2744992965","https://openalex.org/W2751368657","https://openalex.org/W2774014017","https://openalex.org/W2785795994","https://openalex.org/W2796445688","https://openalex.org/W2887874867","https://openalex.org/W2890172403","https://openalex.org/W2894913449","https://openalex.org/W2901892127","https://openalex.org/W2904005001","https://openalex.org/W2905560685","https://openalex.org/W2913170515","https://openalex.org/W2927490830","https://openalex.org/W2963725279","https://openalex.org/W2969102725","https://openalex.org/W2975778935","https://openalex.org/W2979748621","https://openalex.org/W2981595546","https://openalex.org/W2982704408","https://openalex.org/W2995302838","https://openalex.org/W2999571597","https://openalex.org/W3003534375","https://openalex.org/W3005407459","https://openalex.org/W3014564255","https://openalex.org/W3016719748","https://openalex.org/W3033271345","https://openalex.org/W3033557345","https://openalex.org/W3034282764","https://openalex.org/W3042090478","https://openalex.org/W3082143166","https://openalex.org/W3088102248","https://openalex.org/W3114636215","https://openalex.org/W3116822623","https://openalex.org/W3127074460","https://openalex.org/W3128332505","https://openalex.org/W3191407405","https://openalex.org/W3193059835","https://openalex.org/W3198883669","https://openalex.org/W3203590351","https://openalex.org/W4248800565","https://openalex.org/W4249736682"],"related_works":["https://openalex.org/W4287867034","https://openalex.org/W4225274307","https://openalex.org/W3178345791","https://openalex.org/W3108403339","https://openalex.org/W3005783148","https://openalex.org/W2986378528","https://openalex.org/W2162712524","https://openalex.org/W2142924612","https://openalex.org/W2092661960","https://openalex.org/W2023005931"],"abstract_inverted_index":{"Erratic":[0],"seismic":[1,57,88],"noise,":[2],"following":[3],"a":[4,11,83,103,122,138,167,218],"(known":[5],"or":[6],"unknown)":[7],"non-Gaussian":[8],"distribution,":[9],"poses":[10],"formidable":[12],"challenge":[13],"to":[14,36,148,232],"conventional":[15],"methods":[16,49,76],"of":[17,72,86,152,166,173,212,236],"random":[18,67,180],"noise":[19,23,93,118,161,181],"attenuation.":[20],"Many":[21],"erratic":[22,65,92,160],"cancellation":[24],"methods,":[25],"for":[26,116,203,217],"instance,":[27],"robust":[28,63,123,153],"reduced-rank":[29],"and":[30,59,66,94,193,226],"sparsity-promoting":[31],"filtering,":[32],"have":[33],"been":[34],"proven":[35],"achieve":[37],"promising":[38],"results":[39],"in":[40,102,137,171,189],"overcoming":[41],"this":[42,109,157],"challenge.":[43],"Among":[44],"them,":[45],"deep":[46,124],"learning":[47,81],"(DL)":[48],"require":[50],"no":[51],"assumptions":[52],"about":[53],"the":[54,70,129,131,144,150,159,174,179,186,190,194,199,205,210,213,234,237],"underlying":[55],"clear":[56],"image":[58,154],"are":[60,99,207,230],"also":[61],"more":[62],"against":[64],"noise.":[68],"However,":[69],"success":[71],"existing":[73],"DL-based":[74],"denoising":[75],"strongly":[77],"depends":[78],"on":[79,121,209,223],"supervised":[80],"from":[82],"large":[84],"number":[85],"ground-truth":[87],"images":[89],"affected":[90],"by":[91,143,164,184],"their":[95],"clean":[96],"counterparts,":[97],"which":[98],"typically":[100],"unavailable":[101],"real-world":[104],"setting.":[105],"As":[106],"an":[107,112],"alternative,":[108],"article":[110],"presents":[111],"unsupervised":[113],"DL":[114],"method":[115],"erratic-plus-Gaussian":[117],"removal":[119],"based":[120],"convolutional":[125],"autoencoder":[126],"(RDCAE).":[127],"In":[128,156,177],"RDCAE,":[130],"mean":[132,187],"squared":[133],"error":[134],"(mse)":[135],"loss":[136],"classic":[139],"DCAE":[140],"is":[141,162,182],"replaced":[142],"smooth":[145],"Welsch":[146,175,191],"function":[147,192],"exploit":[149],"concept":[151],"denoising.":[155],"way,":[158],"downweighted":[163],"means":[165],"curbed":[168],"weight":[169],"defined":[170],"terms":[172],"function.":[176],"contrast,":[178],"diluted":[183],"combining":[185],"square":[188],"total":[195],"variation":[196],"(TV).":[197],"Subsequently,":[198],"training":[200],"procedures":[201],"required":[202],"solving":[204],"RDCAE":[206],"derived":[208],"basis":[211],"backpropagation":[214],"(BP)":[215],"algorithm":[216],"neural":[219],"network.":[220],"Experiments":[221],"conducted":[222],"both":[224],"synthetic":[225],"real":[227],"field":[228],"datasets":[229],"reported":[231],"illustrate":[233],"efficacy":[235],"proposed":[238],"method.":[239]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4226266787","counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":2}],"updated_date":"2024-11-05T14:55:59.676879","created_date":"2022-05-05"}