{"id":"https://openalex.org/W3133999455","doi":"https://doi.org/10.1109/tgrs.2021.3061438","title":"Seismic Dip Estimation With a Domain Knowledge Constrained Transfer Learning Approach","display_name":"Seismic Dip Estimation With a Domain Knowledge Constrained Transfer Learning Approach","publication_year":2021,"publication_date":"2021-03-10","ids":{"openalex":"https://openalex.org/W3133999455","doi":"https://doi.org/10.1109/tgrs.2021.3061438","mag":"3133999455"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2021.3061438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3061438","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/A5012311963","display_name":"Yile Ao","orcid":"https://orcid.org/0000-0003-0274-7477"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yile Ao","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China","Institute for Artificial Intelligence (THUAI), State Key Laboratory of Intelligent Technology and Systems, Beijing National Research Center for Information Science and Technology (BNRIST), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Institute for Artificial Intelligence (THUAI), State Key Laboratory of Intelligent Technology and Systems, Beijing National Research Center for Information Science and Technology (BNRIST), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011509629","display_name":"Wenkai Lu","orcid":"https://orcid.org/0000-0003-0249-2144"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenkai Lu","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China","Institute for Artificial Intelligence (THUAI), State Key Laboratory of Intelligent Technology and Systems, Beijing National Research Center for Information Science and Technology (BNRIST), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Institute for Artificial Intelligence (THUAI), State Key Laboratory of Intelligent Technology and Systems, Beijing National Research Center for Information Science and Technology (BNRIST), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039377251","display_name":"Pengcheng Xu","orcid":"https://orcid.org/0000-0002-5231-877X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengcheng Xu","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China","Institute for Artificial Intelligence (THUAI), State Key Laboratory of Intelligent Technology and Systems, Beijing National Research Center for Information Science and Technology (BNRIST), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Institute for Artificial Intelligence (THUAI), State Key Laboratory of Intelligent Technology and Systems, Beijing National Research Center for Information Science and Technology (BNRIST), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048853053","display_name":"Bowu Jiang","orcid":"https://orcid.org/0000-0002-9878-6114"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowu Jiang","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China","Institute for Artificial Intelligence (THUAI), State Key Laboratory of Intelligent Technology and Systems, Beijing National Research Center for Information Science and Technology (BNRIST), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Institute for Artificial Intelligence (THUAI), State Key Laboratory of Intelligent Technology and Systems, Beijing National Research Center for Information Science and Technology (BNRIST), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5012311963"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":5.5875,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.97008649,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":1.0,"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":1.0,"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/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/T10635","display_name":"Hydraulic Fracturing and Reservoir Analysis","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/robustness","display_name":"Robustness (evolution)","score":0.7246790528297424},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6417809128761292},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.592540442943573},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5407317876815796},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.5375847816467285},{"id":"https://openalex.org/keywords/knowledge-transfer","display_name":"Knowledge transfer","score":0.47237876057624817},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4594188332557678},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4535244405269623},{"id":"https://openalex.org/keywords/transfer-function","display_name":"Transfer function","score":0.45287051796913147},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.404884934425354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32014966011047363},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09180140495300293}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7246790528297424},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6417809128761292},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.592540442943573},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5407317876815796},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.5375847816467285},{"id":"https://openalex.org/C2776960227","wikidata":"https://www.wikidata.org/wiki/Q2586354","display_name":"Knowledge transfer","level":2,"score":0.47237876057624817},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4594188332557678},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4535244405269623},{"id":"https://openalex.org/C81299745","wikidata":"https://www.wikidata.org/wiki/Q334269","display_name":"Transfer function","level":2,"score":0.45287051796913147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.404884934425354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32014966011047363},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09180140495300293},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2021.3061438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3061438","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/G2518711674","display_name":null,"funder_award_id":"41674116","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3078455064","display_name":null,"funder_award_id":"41974126","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G931848387","display_name":null,"funder_award_id":"2018YFA0702501","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1963613499","https://openalex.org/W1964036986","https://openalex.org/W1964236472","https://openalex.org/W2014758788","https://openalex.org/W2028783597","https://openalex.org/W2036523205","https://openalex.org/W2059084484","https://openalex.org/W2060334695","https://openalex.org/W2063410799","https://openalex.org/W2102777419","https://openalex.org/W2106921281","https://openalex.org/W2107127511","https://openalex.org/W2128497116","https://openalex.org/W2129086878","https://openalex.org/W2129516933","https://openalex.org/W2129793631","https://openalex.org/W2139663179","https://openalex.org/W2161006083","https://openalex.org/W2171923309","https://openalex.org/W2319930207","https://openalex.org/W2395611524","https://openalex.org/W2514560653","https://openalex.org/W2593768305","https://openalex.org/W2613245639","https://openalex.org/W2620161271","https://openalex.org/W2774014017","https://openalex.org/W2808760859","https://openalex.org/W2889733417","https://openalex.org/W2894410771","https://openalex.org/W2899651173","https://openalex.org/W2911424749","https://openalex.org/W2915004230","https://openalex.org/W2947853264","https://openalex.org/W2954996726","https://openalex.org/W2963285578","https://openalex.org/W2963403405","https://openalex.org/W2963787510","https://openalex.org/W2963881378","https://openalex.org/W2963941635","https://openalex.org/W2967392291","https://openalex.org/W2968094316","https://openalex.org/W2968906670","https://openalex.org/W2969839555","https://openalex.org/W2979419929","https://openalex.org/W2982350982","https://openalex.org/W2995504702","https://openalex.org/W2999905431","https://openalex.org/W3005407459","https://openalex.org/W3014923544","https://openalex.org/W3034362861","https://openalex.org/W3042090478","https://openalex.org/W3081502560","https://openalex.org/W3084225545","https://openalex.org/W3089802572","https://openalex.org/W3098108457","https://openalex.org/W3099006605","https://openalex.org/W3102755745","https://openalex.org/W3117351614","https://openalex.org/W3164561618","https://openalex.org/W3174765192","https://openalex.org/W4210972068","https://openalex.org/W6685562342","https://openalex.org/W6750109254","https://openalex.org/W6754770232","https://openalex.org/W7014673677"],"related_works":["https://openalex.org/W3201126466","https://openalex.org/W4282827391","https://openalex.org/W3165580226","https://openalex.org/W4386828785","https://openalex.org/W3135401135","https://openalex.org/W2886688859","https://openalex.org/W3133164560","https://openalex.org/W3041001745","https://openalex.org/W4224526119","https://openalex.org/W3133987783"],"abstract_inverted_index":{"Accurate":[0],"estimation":[1,159,229,288],"of":[2,7,21,81,191,225,233],"volumetric":[3],"seismic":[4,12,31,74,99,114,124,139,163,175,199,227,261,286],"dip":[5,32,91,103,158,228,287],"is":[6,43,96],"great":[8,51],"significance":[9],"for":[10,30,151,249,284],"subsequent":[11],"processing":[13],"and":[14,55,68,79,116,122,167,195,212,240,252,259,290],"interpretation":[15],"works.":[16],"Recently,":[17],"with":[18,35,40,101,177],"the":[19,72,77,88,111,120,137,157,172,184,189,223,226,234,246,256,269,275,291,304],"development":[20],"deep":[22,192,296],"learning":[23,149,193,216,224,297],"techniques,":[24],"convolutional":[25,41],"networks":[26,42,70,83,126],"are":[27,84,218,242],"also":[28,49,187,300],"applied":[29],"estimation.":[33],"Compared":[34],"traditional":[36,64],"approaches,":[37],"estimating":[38],"dips":[39,61,248],"not":[44],"only":[45],"more":[46],"efficient":[47],"but":[48],"shows":[50],"promise":[52],"in":[53,90,113,198,237,268,303],"accuracy":[54,78],"robustness.":[56],"However,":[57,105],"if":[58],"we":[59,106,145],"take":[60],"estimated":[62,247],"by":[63,244],"approaches":[65],"as":[66,204],"labels":[67],"train":[69],"on":[71,136,161,255],"field":[73,123,138,174],"data":[75,176],"directly,":[76],"robustness":[80],"learned":[82,128],"influenced":[85],"due":[86,109],"to":[87,110,171],"error":[89],"labels.":[92,104],"An":[93],"alternative":[94],"solution":[95],"synthesizing":[97],"realistic":[98],"samples":[100,131,164],"accurate":[102],"find":[107],"that":[108,274],"differences":[112],"responses":[115],"structural":[117,250],"patterns":[118],"between":[119],"synthetic":[121,130,162],"data,":[125,262],"directly":[127],"from":[129],"cannot":[132],"guarantee":[133],"their":[134],"generalization":[135],"data.":[140],"To":[141],"overcome":[142],"these":[143],"drawbacks,":[144],"develop":[146],"a":[147,178],"transfer":[148,215],"approach":[150,155,186,236,277],"improvement.":[152],"The":[153,231],"proposed":[154,185,235,276],"pretrains":[156],"network":[160],"at":[165],"first":[166],"then":[168],"transfers":[169],"it":[170],"targeted":[173],"domain":[179,196,293],"knowledge-inspired":[180],"fine-tuning":[181],"process.":[182],"Moreover,":[183],"highlights":[188],"combination":[190],"techniques":[194],"knowledge":[197,208,213,294],"processing\u2014several":[200],"subtle":[201],"realizations,":[202],"such":[203],"knowledge-driven":[205],"sample":[206],"augmentation,":[207],"constrained":[209,295],"loss":[210],"function,":[211],"motivated":[214],"strategy,":[217],"introduced,":[219],"which":[220,263],"greatly":[221],"enhance":[222],"network.":[230],"advantages":[232],"accuracy,":[238],"robustness,":[239],"resolution":[241],"validated":[243],"applying":[245],"filtering":[251],"curvature":[253],"extraction":[254],"Netherlands":[257],"F3":[258],"Kerry3D":[260],"further":[264,285],"confirms":[265],"its":[266],"practicality":[267],"real-world":[270],"application.":[271],"We":[272],"believe":[273],"has":[278],"provided":[279],"an":[280],"effective":[281],"improved":[282],"way":[283],"practices,":[289],"present":[292],"case":[298],"will":[299],"inspire":[301],"researchers":[302],"same":[305],"discipline.":[306]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}