{"id":"https://openalex.org/W4392509048","doi":"https://doi.org/10.3390/rs16050922","title":"Improving Seismic Fault Recognition with Self-Supervised Pre-Training: A Study of 3D Transformer-Based with Multi-Scale Decoding and Fusion","display_name":"Improving Seismic Fault Recognition with Self-Supervised Pre-Training: A Study of 3D Transformer-Based with Multi-Scale Decoding and Fusion","publication_year":2024,"publication_date":"2024-03-06","ids":{"openalex":"https://openalex.org/W4392509048","doi":"https://doi.org/10.3390/rs16050922"},"language":"en","primary_location":{"id":"doi:10.3390/rs16050922","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16050922","pdf_url":"https://www.mdpi.com/2072-4292/16/5/922/pdf?version=1709715286","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/16/5/922/pdf?version=1709715286","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055103553","display_name":"Zeren Zhang","orcid":"https://orcid.org/0000-0003-0573-0339"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeren Zhang","raw_affiliation_strings":["Department of Information and Computational Sciences, School of Mathematical Sciences, Peking University, Beijing 100871, China"],"affiliations":[{"raw_affiliation_string":"Department of Information and Computational Sciences, School of Mathematical Sciences, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102007154","display_name":"Ran Chen","orcid":"https://orcid.org/0009-0007-9121-9647"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Chen","raw_affiliation_strings":["Department of Information and Computational Sciences, School of Mathematical Sciences, Peking University, Beijing 100871, China"],"affiliations":[{"raw_affiliation_string":"Department of Information and Computational Sciences, School of Mathematical Sciences, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067164993","display_name":"Jinwen Ma","orcid":"https://orcid.org/0000-0002-7388-4295"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinwen Ma","raw_affiliation_strings":["Department of Information and Computational Sciences, School of Mathematical Sciences, Peking University, Beijing 100871, China"],"affiliations":[{"raw_affiliation_string":"Department of Information and Computational Sciences, School of Mathematical Sciences, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5067164993"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":10.9151,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.99121233,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"16","issue":"5","first_page":"922","last_page":"922"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.994700014591217,"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 Imaging and Inversion Techniques","score":0.994700014591217,"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/T13018","display_name":"Seismology and Earthquake Studies","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10892","display_name":"Drilling and Well Engineering","score":0.9868000149726868,"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/computer-science","display_name":"Computer science","score":0.5275801420211792},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5210292339324951},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4481453597545624},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.43660420179367065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4171741008758545},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.413161963224411},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.36573606729507446},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.11529430747032166},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10052564740180969},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.06737658381462097},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.0637812614440918},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.051944345235824585}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5275801420211792},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5210292339324951},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4481453597545624},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.43660420179367065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4171741008758545},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.413161963224411},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.36573606729507446},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.11529430747032166},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10052564740180969},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.06737658381462097},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0637812614440918},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.051944345235824585},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs16050922","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16050922","pdf_url":"https://www.mdpi.com/2072-4292/16/5/922/pdf?version=1709715286","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1d6d37d21f624f1bb33e2d4fc8fdc8cf","is_oa":true,"landing_page_url":"https://doaj.org/article/1d6d37d21f624f1bb33e2d4fc8fdc8cf","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 16, Iss 5, p 922 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs16050922","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16050922","pdf_url":"https://www.mdpi.com/2072-4292/16/5/922/pdf?version=1709715286","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321570","display_name":"China National Petroleum Corporation","ror":"https://ror.org/05269d038"},{"id":"https://openalex.org/F4320324787","display_name":"Peking University","ror":"https://ror.org/02v51f717"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4392509048.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1970193144","https://openalex.org/W1973093491","https://openalex.org/W1973289968","https://openalex.org/W2020704676","https://openalex.org/W2036895509","https://openalex.org/W2082304646","https://openalex.org/W2108598243","https://openalex.org/W2122327629","https://openalex.org/W2161006083","https://openalex.org/W2208968870","https://openalex.org/W2278767355","https://openalex.org/W2298012029","https://openalex.org/W2313011567","https://openalex.org/W2322036057","https://openalex.org/W2891111066","https://openalex.org/W2892287369","https://openalex.org/W2911424749","https://openalex.org/W2979352041","https://openalex.org/W2982350982","https://openalex.org/W3005680577","https://openalex.org/W3095319910","https://openalex.org/W3138516171","https://openalex.org/W3153344593","https://openalex.org/W3169279223","https://openalex.org/W4212875960","https://openalex.org/W4244567635","https://openalex.org/W4248461486","https://openalex.org/W4283707319","https://openalex.org/W4286906176","https://openalex.org/W4287887114","https://openalex.org/W4308883462","https://openalex.org/W4312428231","https://openalex.org/W4312804044","https://openalex.org/W4313156423","https://openalex.org/W4320712967","https://openalex.org/W4320920694","https://openalex.org/W4360869627","https://openalex.org/W4365129605","https://openalex.org/W4384937344","https://openalex.org/W4385603727","https://openalex.org/W4388145572","https://openalex.org/W4390874575","https://openalex.org/W4391563516","https://openalex.org/W6774314701","https://openalex.org/W6840275681","https://openalex.org/W6851953984"],"related_works":["https://openalex.org/W2099421762","https://openalex.org/W2530546662","https://openalex.org/W2967030268","https://openalex.org/W2185253430","https://openalex.org/W4210345652","https://openalex.org/W3205103124","https://openalex.org/W1984333081","https://openalex.org/W2945063165","https://openalex.org/W2205042400","https://openalex.org/W2090790166"],"abstract_inverted_index":{"Seismic":[0],"fault":[1,18,73,88,174,188],"interpretation":[2],"holds":[3],"great":[4],"significance":[5],"in":[6,207],"the":[7,47,57,76,93,113,119,139,166,176,201],"fields":[8],"of":[9,16,51,59,78,121],"geophysics":[10],"and":[11,40,49,83,124,129,151,185],"geology.":[12],"However,":[13],"conventional":[14],"methods":[15,70,86],"seismic":[17,38,72,122],"recognition":[19,89,135],"encounter":[20],"various":[21,144],"issues.":[22],"For":[23],"example,":[24],"models":[25],"trained":[26],"on":[27,46,87,118,199],"synthetic":[28],"data":[29,123],"often":[30],"exhibit":[31],"inadequate":[32],"generalization":[33],"when":[34,181],"applied":[35],"to":[36,56,71,95,172],"field":[37],"data,":[39,53],"supervised":[41],"learning":[42,155],"is":[43],"heavily":[44],"dependent":[45],"quantity":[48],"quality":[50],"annotated":[52,205],"being":[54],"susceptible":[55],"subjectivity":[58],"interpreters.":[60],"To":[61],"address":[62],"these":[63],"challenges,":[64],"we":[65,106,142],"propose":[66,107],"applying":[67],"self-supervised":[68,154],"pre-training":[69,85,110,140],"recognition,":[74],"exploring":[75],"transfer":[77],"3D":[79],"Transformer-based":[80],"backbone":[81],"networks":[82],"different":[84],"tasks,":[90],"thereby":[91],"enabling":[92],"model":[94,177],"learn":[96],"more":[97],"powerful":[98],"feature":[99],"representations":[100],"from":[101],"extensive":[102],"unlabeled":[103],"datasets.":[104],"Additionally,":[105],"an":[108],"innovative":[109],"strategy":[111],"for":[112],"entire":[114],"segmentation":[115],"network":[116],"based":[117],"characteristics":[120],"introduce":[125],"a":[126,152],"multi-scale":[127,159],"decoding":[128,160],"fusion":[130],"module":[131],"that":[132,192],"significantly":[133],"improves":[134],"accuracy.":[136],"Specifically,":[137],"during":[138,165],"stage,":[141],"compare":[143],"self-supervision":[145],"methods,":[146],"like":[147],"MAE,":[148],"SimMIM,":[149],"SimCLR,":[150],"joint":[153],"approach.":[156],"We":[157],"adopt":[158],"step-by-step":[161],"fitting":[162],"expansion":[163],"targets":[164],"fine-tuning":[167],"stage.":[168],"Ultimately":[169],"merging":[170],"features":[171],"refine":[173],"edges,":[175],"displays":[178],"superior":[179],"adaptability":[180],"handling":[182],"narrow,":[183],"elongated,":[184],"unevenly":[186],"distributed":[187],"annotations.":[189],"Experiments":[190],"demonstrate":[191],"our":[193],"proposed":[194],"method":[195],"achieves":[196],"state-of-the-art":[197],"performance":[198],"Thebe,":[200],"currently":[202],"largest":[203],"publicly":[204],"dataset":[206],"this":[208],"field.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":7}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}