{"id":"https://openalex.org/W4415125579","doi":"https://doi.org/10.1109/tgrs.2025.3620531","title":"DP-TTA: Test-Time Adaptation for Transient Electromagnetic Signal Denoising via Dictionary-Driven Prior Regularization","display_name":"DP-TTA: Test-Time Adaptation for Transient Electromagnetic Signal Denoising via Dictionary-Driven Prior Regularization","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415125579","doi":"https://doi.org/10.1109/tgrs.2025.3620531"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3620531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3620531","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/A5111920187","display_name":"Meng Yang","orcid":"https://orcid.org/0009-0009-7824-7306"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Meng Yang","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Chengdu University of Technology, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Chengdu University of Technology, Chengdu, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020579227","display_name":"Kecheng Chen","orcid":"https://orcid.org/0000-0001-6657-3221"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kecheng Chen","raw_affiliation_strings":["Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Luo","orcid":"https://orcid.org/0009-0002-7905-2251"},"institutions":[{"id":"https://openalex.org/I4210091467","display_name":"Sichuan Provincial Architectural Design and Research Institute (China)","ror":"https://ror.org/00eqa6a26","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091467"]},{"id":"https://openalex.org/I4210099931","display_name":"Sichuan Highway Design and Research Institute","ror":"https://ror.org/012hbj192","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210099931"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Luo","raw_affiliation_strings":["Sichuan Provincial Natural Resources Survey and Design Group Company Ltd., Chengdu, Sichuan, China","Sichuan Provincial Natural Resources Survey and Design Group Co., Ltd., China"],"affiliations":[{"raw_affiliation_string":"Sichuan Provincial Natural Resources Survey and Design Group Company Ltd., Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I4210099931","https://openalex.org/I4210091467"]},{"raw_affiliation_string":"Sichuan Provincial Natural Resources Survey and Design Group Co., Ltd., China","institution_ids":["https://openalex.org/I4210099931"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102389389","display_name":"Xianjie Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091467","display_name":"Sichuan Provincial Architectural Design and Research Institute (China)","ror":"https://ror.org/00eqa6a26","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091467"]},{"id":"https://openalex.org/I4210099931","display_name":"Sichuan Highway Design and Research Institute","ror":"https://ror.org/012hbj192","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210099931"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianjie Chen","raw_affiliation_strings":["Sichuan Provincial Natural Resources Survey and Design Group Company Ltd., Chengdu, Sichuan, China","Sichuan Provincial Natural Resources Survey and Design Group Co., Ltd., Chengdu University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Sichuan Provincial Natural Resources Survey and Design Group Company Ltd., Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I4210099931","https://openalex.org/I4210091467"]},{"raw_affiliation_string":"Sichuan Provincial Natural Resources Survey and Design Group Co., Ltd., Chengdu University of Technology, China","institution_ids":["https://openalex.org/I4210091467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025737507","display_name":"Yong Jia","orcid":"https://orcid.org/0000-0003-3165-3349"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Jia","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Chengdu University of Technology, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Chengdu University of Technology, Chengdu, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mingyue Wang","orcid":"https://orcid.org/0009-0003-8663-920X"},"institutions":[{"id":"https://openalex.org/I51158804","display_name":"Massey University","ror":"https://ror.org/052czxv31","country_code":"NZ","type":"education","lineage":["https://openalex.org/I51158804"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Mingyue Wang","raw_affiliation_strings":["School of Mathematical and Computational Sciences, Massey University, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"School of Mathematical and Computational Sciences, Massey University, Auckland, New Zealand","institution_ids":["https://openalex.org/I51158804"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062227306","display_name":"Fanqiang Lin","orcid":"https://orcid.org/0000-0003-4884-1944"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fanqiang Lin","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Chengdu University of Technology, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Chengdu University of Technology, Chengdu, China","institution_ids":["https://openalex.org/I31595395"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5111920187"],"corresponding_institution_ids":["https://openalex.org/I31595395"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3241092,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9922999739646912,"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"}},{"id":"https://openalex.org/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9789000153541565,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6990000009536743},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.669700026512146},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5253999829292297},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.49959999322891235},{"id":"https://openalex.org/keywords/transient","display_name":"Transient (computer programming)","score":0.49390000104904175},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4862000048160553},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.37770000100135803},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.37279999256134033},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.3653999865055084}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7504000067710876},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6990000009536743},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.669700026512146},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5253999829292297},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.49959999322891235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4975999891757965},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.49390000104904175},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4862000048160553},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.37770000100135803},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.37279999256134033},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C2909720056","wikidata":"https://www.wikidata.org/wiki/Q11406","display_name":"Electromagnetics","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3522000014781952},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.33009999990463257},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30720001459121704},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2992999851703644},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.2867000102996826},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C2986577269","wikidata":"https://www.wikidata.org/wiki/Q11306265","display_name":"Random noise","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3620531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3620531","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/G1823251838","display_name":null,"funder_award_id":"2023-JB00-00032-GX","funder_id":"https://openalex.org/F4320336753","funder_display_name":"Changsha Science and Technology Project"}],"funders":[{"id":"https://openalex.org/F4320336753","display_name":"Changsha Science and Technology Project","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W2017326891","https://openalex.org/W2157209869","https://openalex.org/W2160547390","https://openalex.org/W2194775991","https://openalex.org/W2225156818","https://openalex.org/W2508457857","https://openalex.org/W2520936856","https://openalex.org/W2594993572","https://openalex.org/W2895190937","https://openalex.org/W2921298990","https://openalex.org/W3020865293","https://openalex.org/W3104899156","https://openalex.org/W3180288799","https://openalex.org/W3180993110","https://openalex.org/W3191430529","https://openalex.org/W3198159016","https://openalex.org/W3200526976","https://openalex.org/W4210696675","https://openalex.org/W4213031592","https://openalex.org/W4237444302","https://openalex.org/W4281785213","https://openalex.org/W4289950750","https://openalex.org/W4312365002","https://openalex.org/W4313156423","https://openalex.org/W4319300052","https://openalex.org/W4382365350","https://openalex.org/W4382769518","https://openalex.org/W4385800613","https://openalex.org/W4385812021","https://openalex.org/W4386076152","https://openalex.org/W4388642393","https://openalex.org/W4388755586","https://openalex.org/W4390874837","https://openalex.org/W4392154905","https://openalex.org/W4392405852","https://openalex.org/W4392518450","https://openalex.org/W4400767051","https://openalex.org/W4402716191","https://openalex.org/W4402916326","https://openalex.org/W4402916448","https://openalex.org/W4403387672","https://openalex.org/W4404769928","https://openalex.org/W4405287591","https://openalex.org/W4405718304","https://openalex.org/W4406457766","https://openalex.org/W4406457825","https://openalex.org/W4409369839"],"related_works":[],"abstract_inverted_index":{"Transient":[0],"Electromagnetic":[1],"(TEM)":[2],"method":[3,229],"is":[4,106,186],"widely":[5],"used":[6],"in":[7,24,55,65,73,79,158],"various":[8,25],"geophysical":[9],"applications,":[10],"providing":[11],"valuable":[12],"insights":[13],"into":[14,188],"subsurface":[15],"properties.":[16],"However,":[17],"time-domain":[18],"TEM":[19,108,236],"signals":[20,109],"are":[21,41],"often":[22,68],"submerged":[23],"types":[26],"of":[27,127],"noise.":[28],"While":[29],"recent":[30],"deep":[31],"learning-based":[32],"denoising":[33,89,156,237],"models":[34,40,63],"have":[35],"shown":[36],"strong":[37],"performance,":[38],"these":[39,178],"mostly":[42],"trained":[43,64],"on":[44],"simulated":[45],"or":[46],"single":[47],"real-world":[48],"scenario":[49],"data,":[50],"overlooking":[51],"the":[52,96,140,145,189,194,200,214,218,227],"significant":[53],"differences":[54,78],"noise":[56],"characteristics":[57,132,180],"from":[58,213],"different":[59,124],"geographical":[60],"regions.":[61],"Intuitively,":[62],"one":[66],"environment":[67],"struggle":[69],"to":[70,77,87,176,202,205],"perform":[71],"well":[72],"new":[74,159,206],"settings":[75],"due":[76],"geological":[80],"conditions,":[81],"equipment,":[82],"and":[83,118,217,239],"external":[84,128],"interference,":[85],"leading":[86],"reduced":[88],"performance.":[90],"To":[91,161],"this":[92,197],"end,":[93],"we":[94,164,171],"propose":[95],"Dictionary-driven":[97],"Prior":[98],"Regularization":[99],"Test-time":[100],"Adaptation":[101],"(DP-TTA).":[102],"Our":[103],"key":[104],"insight":[105],"that":[107,226],"possess":[110],"intrinsic":[111,131,179],"physical":[112],"characteristics,":[113],"such":[114],"as":[115,134,181],"exponential":[116],"decay":[117],"smoothness,":[119],"which":[120,143,185],"remain":[121],"consistent":[122],"across":[123],"regions":[125],"regardless":[126],"conditions.":[129],"These":[130],"serve":[133],"ideal":[135],"prior":[136,198],"knowledge":[137],"for":[138],"guiding":[139],"TTA":[141,240],"strategy,":[142],"helps":[144],"pre-trained":[146],"model":[147,190,201],"dynamically":[148,204],"adjust":[149],"parameters":[150],"by":[151,208],"utilizing":[152],"self-supervised":[153,210],"losses,":[154],"improving":[155],"performance":[157,233],"scenarios.":[160],"implement":[162],"this,":[163],"customized":[165],"a":[166,182],"network,":[167],"named":[168],"DTEMDNet.":[169],"Specifically,":[170],"first":[172],"use":[173],"dictionary":[174],"learning":[175],"encode":[177],"dictionary-driven":[183,215],"prior,":[184],"integrated":[187],"during":[191],"training.":[192],"At":[193],"testing":[195],"stage,":[196],"guides":[199],"adapt":[203],"environments":[207],"minimizing":[209],"losses":[211],"derived":[212],"consistency":[216],"signal":[219],"one-order":[220],"variation.":[221],"Extensive":[222],"experimental":[223],"results":[224],"demonstrate":[225],"proposed":[228],"achieves":[230],"much":[231],"better":[232],"than":[234],"existing":[235],"methods":[238],"methods.":[241]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-14T00:00:00"}
