{"id":"https://openalex.org/W4361990957","doi":"https://doi.org/10.1109/tgrs.2023.3262835","title":"Uncertainty Quantification in Intelligent-Based Electrical Resistivity Tomography Image Reconstruction With Monte Carlo Dropout Strategy","display_name":"Uncertainty Quantification in Intelligent-Based Electrical Resistivity Tomography Image Reconstruction With Monte Carlo Dropout Strategy","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4361990957","doi":"https://doi.org/10.1109/tgrs.2023.3262835"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3262835","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3262835","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/A5097901643","display_name":"Lan Xixi","orcid":"https://orcid.org/0000-0001-9189-4721"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lan Xixi","raw_affiliation_strings":["School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041439668","display_name":"Changchun Zou","orcid":"https://orcid.org/0000-0003-4305-5055"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changchun Zou","raw_affiliation_strings":["School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031123838","display_name":"Cheng Peng","orcid":"https://orcid.org/0000-0002-2174-7811"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Peng","raw_affiliation_strings":["School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036118111","display_name":"Caowei Wu","orcid":"https://orcid.org/0000-0001-9059-4508"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caowei Wu","raw_affiliation_strings":["School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5097901643"],"corresponding_institution_ids":["https://openalex.org/I3125743391"],"apc_list":null,"apc_paid":null,"fwci":4.739,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.95541502,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10572","display_name":"Geophysical and Geoelectrical Methods","score":0.9998999834060669,"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/T10572","display_name":"Geophysical and Geoelectrical Methods","score":0.9998999834060669,"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9991999864578247,"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/monte-carlo-method","display_name":"Monte Carlo method","score":0.6929579973220825},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.6376157999038696},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6189149618148804},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.5354499816894531},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.5089123249053955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4890364110469818},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48613449931144714},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.4840835630893707},{"id":"https://openalex.org/keywords/tomography","display_name":"Tomography","score":0.43047675490379333},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.42414969205856323},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.40884989500045776},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30044305324554443},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17117169499397278},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15218451619148254},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11984637379646301},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.11695694923400879},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0833510160446167}],"concepts":[{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6929579973220825},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.6376157999038696},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6189149618148804},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.5354499816894531},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.5089123249053955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4890364110469818},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48613449931144714},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.4840835630893707},{"id":"https://openalex.org/C163716698","wikidata":"https://www.wikidata.org/wiki/Q841267","display_name":"Tomography","level":2,"score":0.43047675490379333},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.42414969205856323},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.40884989500045776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30044305324554443},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17117169499397278},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15218451619148254},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11984637379646301},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.11695694923400879},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0833510160446167},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3262835","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3262835","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":[],"awards":[{"id":"https://openalex.org/G2312932803","display_name":null,"funder_award_id":"42274232","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5940355250","display_name":null,"funder_award_id":"41874215","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":69,"referenced_works":["https://openalex.org/W1901616594","https://openalex.org/W1913261780","https://openalex.org/W1969362494","https://openalex.org/W1977772221","https://openalex.org/W1996225593","https://openalex.org/W2008616364","https://openalex.org/W2035010137","https://openalex.org/W2043587543","https://openalex.org/W2061980133","https://openalex.org/W2074567512","https://openalex.org/W2087452412","https://openalex.org/W2095534447","https://openalex.org/W2095705004","https://openalex.org/W2111959010","https://openalex.org/W2158433798","https://openalex.org/W2172220975","https://openalex.org/W2180552781","https://openalex.org/W2312542809","https://openalex.org/W2340110837","https://openalex.org/W2508791736","https://openalex.org/W2530307286","https://openalex.org/W2587122419","https://openalex.org/W2751217946","https://openalex.org/W2805286334","https://openalex.org/W2806377087","https://openalex.org/W2884428084","https://openalex.org/W2896344704","https://openalex.org/W2906386705","https://openalex.org/W2906429723","https://openalex.org/W2915004230","https://openalex.org/W2937350470","https://openalex.org/W2963697299","https://openalex.org/W2965510524","https://openalex.org/W2971788173","https://openalex.org/W2981188723","https://openalex.org/W2986624057","https://openalex.org/W2988434973","https://openalex.org/W3002846426","https://openalex.org/W3004301774","https://openalex.org/W3014596384","https://openalex.org/W3016274159","https://openalex.org/W3022423293","https://openalex.org/W3046520725","https://openalex.org/W3099006605","https://openalex.org/W3102100346","https://openalex.org/W3104564825","https://openalex.org/W3118249763","https://openalex.org/W3124594475","https://openalex.org/W3125671608","https://openalex.org/W3127503638","https://openalex.org/W3134774296","https://openalex.org/W3147262955","https://openalex.org/W3164731060","https://openalex.org/W3169976860","https://openalex.org/W3180523341","https://openalex.org/W3187830063","https://openalex.org/W3190174881","https://openalex.org/W3197851495","https://openalex.org/W3197979987","https://openalex.org/W3203774316","https://openalex.org/W3211324228","https://openalex.org/W4205785070","https://openalex.org/W4220686733","https://openalex.org/W4249642108","https://openalex.org/W4252166064","https://openalex.org/W4285307338","https://openalex.org/W6659378910","https://openalex.org/W6674330103","https://openalex.org/W6767293667"],"related_works":["https://openalex.org/W1991093342","https://openalex.org/W2078622645","https://openalex.org/W2170798819","https://openalex.org/W3127311823","https://openalex.org/W1928301487","https://openalex.org/W2151220638","https://openalex.org/W2725829804","https://openalex.org/W3123380534","https://openalex.org/W4301368605","https://openalex.org/W4297623270"],"abstract_inverted_index":{"The":[0,166],"Electrical":[1],"Resistivity":[2],"Tomography":[3],"(ERT)":[4],"method":[5,129],"plays":[6],"an":[7],"essential":[8],"role":[9],"in":[10,193],"researching":[11],"electrical":[12],"properties":[13],"at":[14],"the":[15,19,26,36,43,52,70,93,112,115,121,139,153,178,185,198,204,214,225],"core":[16],"scale,":[17],"and":[18,42,146,189],"resistivity":[20],"image":[21,74,117,145,148],"inversion":[22,53,75,167,236],"reconstruction":[23,97,118],"technique":[24],"is":[25,149,229],"key":[27],"to":[28,64,80,109,130,151,216],"constraining":[29],"measurement":[30],"accuracy.":[31],"In":[32,99],"recent":[33],"years,":[34],"with":[35,125],"improvement":[37],"of":[38,45,49,72,95,114,155,158,175,180,187,213,230],"computer":[39],"operation":[40],"capabilities":[41],"acquisition":[44],"a":[46,104,126,211],"large":[47,77],"amount":[48],"geophysical":[50],"data,":[51],"algorithms":[54],"represented":[55],"by":[56,119,162,201],"machine":[57],"learning":[58],"(ML)":[59],"have":[60],"made":[61],"it":[62],"possible":[63],"reconstruct":[65],"ERT":[66,73,116,226],"images":[67,220],"automatically.":[68],"However,":[69],"solution":[71],"has":[76],"uncertainty":[78,94,113,215],"due":[79],"high":[81],"nonlinearity.":[82],"Meanwhile,":[83],"traditional":[84],"ML":[85,107,164],"methods":[86],"are":[87,221],"not":[88],"initially":[89],"developed":[90],"for":[91,233],"evaluating":[92],"such":[96],"results.":[98],"this":[100,194],"paper,":[101],"we":[102,207],"propose":[103],"novel":[105],"MC-Net":[106,171],"scheme":[108],"quantitatively":[110],"estimate":[111],"introducing":[120],"Monte-Carlo":[122],"Dropout":[123],"strategy":[124],"multiple":[127],"stochastic":[128],"approximate":[131],"Bayesian":[132],"inference.":[133],"As":[134],"one":[135],"important":[136],"evaluation":[137],"index,":[138],"correlation":[140],"coefficient":[141],"(CC)":[142],"between":[143],"target":[144],"reconstructed":[147,219],"used":[150],"compare":[152],"effects":[154],"six":[156],"types":[157],"simulated":[159],"data":[160],"carried":[161],"different":[163],"schemes.":[165],"results":[168,191],"show":[169],"that":[170],"increases":[172],"lower":[173],"limit":[174],"CC":[176],"on":[177],"premise":[179],"ensuring":[181],"average":[182],"CC.":[183],"Moreover,":[184],"accuracy":[186],"regression":[188],"classification":[190],"defined":[192],"paper":[195],"also":[196],"obtained":[197],"highest":[199],"value":[200],"MC-Net.":[202],"With":[203],"proposed":[205],"scheme,":[206],"can":[208],"further":[209],"provide":[210],"quantification":[212],"determine":[217],"whether":[218],"reliable":[222],"after":[223],"reconstructing":[224],"images,":[227],"which":[228],"great":[231],"significance":[232],"actual":[234],"intelligent":[235],"tasks.":[237]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}