{"id":"https://openalex.org/W4206464250","doi":"https://doi.org/10.1109/lgrs.2021.3139329","title":"Fast Dictionary Learning With Automatic Atom Classification for Seismic Data Denoising","display_name":"Fast Dictionary Learning With Automatic Atom Classification for Seismic Data Denoising","publication_year":2021,"publication_date":"2021-12-30","ids":{"openalex":"https://openalex.org/W4206464250","doi":"https://doi.org/10.1109/lgrs.2021.3139329"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2021.3139329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2021.3139329","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5101641155","display_name":"Zhenjie Feng","orcid":"https://orcid.org/0000-0002-9986-7856"},"institutions":[{"id":"https://openalex.org/I4210146051","display_name":"Anyang Institute of Technology","ror":"https://ror.org/03sd3t490","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210146051"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenjie Feng","raw_affiliation_strings":["School of Computer Science and Information Engineering, Anyang Institute of Technology, Anyang, China"],"raw_orcid":"https://orcid.org/0000-0002-9986-7856","affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Engineering, Anyang Institute of Technology, Anyang, China","institution_ids":["https://openalex.org/I4210146051"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101641155"],"corresponding_institution_ids":["https://openalex.org/I4210146051"],"apc_list":null,"apc_paid":null,"fwci":0.1863,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53252057,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9998999834060669,"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","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/T11757","display_name":"Seismic Waves and Analysis","score":0.9993000030517578,"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":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.7411856651306152},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6899222731590271},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6389593482017517},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.6055970191955566},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.5390784740447998},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.48657262325286865},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46668633818626404},{"id":"https://openalex.org/keywords/atom","display_name":"Atom (system on chip)","score":0.46519291400909424},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.45483797788619995},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4314819574356079},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.43096035718917847},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42267265915870667},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.2363278865814209},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20046961307525635},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12017160654067993},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.0796436071395874}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.7411856651306152},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6899222731590271},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6389593482017517},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.6055970191955566},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.5390784740447998},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.48657262325286865},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46668633818626404},{"id":"https://openalex.org/C58312451","wikidata":"https://www.wikidata.org/wiki/Q4817200","display_name":"Atom (system on chip)","level":2,"score":0.46519291400909424},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.45483797788619995},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4314819574356079},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.43096035718917847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42267265915870667},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.2363278865814209},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20046961307525635},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12017160654067993},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0796436071395874},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2021.3139329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2021.3139329","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1853998970","https://openalex.org/W2016572604","https://openalex.org/W2021734622","https://openalex.org/W2082114499","https://openalex.org/W2099321050","https://openalex.org/W2115549875","https://openalex.org/W2282024151","https://openalex.org/W2329945299","https://openalex.org/W2579302569","https://openalex.org/W3095311070","https://openalex.org/W3112872925","https://openalex.org/W6677446445"],"related_works":["https://openalex.org/W1971373099","https://openalex.org/W2078080292","https://openalex.org/W2583520174","https://openalex.org/W2364118486","https://openalex.org/W2102075063","https://openalex.org/W2111634407","https://openalex.org/W2030972733","https://openalex.org/W2084716923","https://openalex.org/W2328330214","https://openalex.org/W204290405"],"abstract_inverted_index":{"Seismic":[0],"noise":[1,27,144],"attenuation":[2],"is":[3,110,146,156,168],"a":[4,46,86,140,150],"long-standing":[5],"yet":[6],"still":[7],"challenging":[8],"topic":[9],"in":[10,45,55,122,188],"seismic":[11,43,58],"data":[12,44],"processing.":[13],"Dictionary":[14],"learning":[15],"(DL)":[16],"has":[17],"emerged":[18],"as":[19,102],"an":[20],"effective":[21],"way":[22],"to":[23,61,103,171],"attenuate":[24],"spatially":[25],"incoherent":[26],"without":[28],"damaging":[29],"useful":[30],"signals.":[31],"DL":[32],"can":[33,52],"adaptively":[34],"learn":[35],"atoms":[36,69,77,94,121,138],"that":[37,78],"best":[38],"represent":[39],"the":[40,62,67,97,105,116,120,135,154,173,182,185],"structure":[41],"of":[42,64,115,119,137,143,184],"fully":[47],"data-driven":[48],"way,":[49],"and":[50,129,161,191],"thus":[51],"be":[53,71],"applied":[54],"arbitrarily":[56],"complex":[57],"datasets.":[59,193],"Due":[60],"existence":[63],"strong":[65],"noise,":[66],"dictionary":[68,165],"could":[70],"strongly":[72],"affected,":[73],"e.g.,":[74,125],"containing":[75],"many":[76],"show":[79],"quite":[80],"irregular":[81,130],"structures.":[82],"Here,":[83],"we":[84],"propose":[85],"new":[87],"method":[88,187],"for":[89,158],"effectively":[90],"rejecting":[91],"those":[92],"noise-contaminated":[93],"while":[95],"maintaining":[96],"most":[98],"representative":[99],"atoms,":[100],"so":[101],"improve":[104],"denoising":[106],"performance.":[107],"Atom":[108],"classification":[109],"performed":[111],"by":[112,149],"taking":[113],"advantage":[114],"statistical":[117],"features":[118],"each":[123],"category,":[124],"regular":[126],"(for":[127,131],"signal)":[128],"noise).":[132],"More":[133],"importantly,":[134],"rejection":[136],"with":[139],"high":[141],"probability":[142],"inference":[145],"controlled":[147],"easily":[148],"threshold,":[151],"below":[152],"which":[153],"atom":[155],"preserved":[157],"sparse":[159],"coding":[160],"denoising.":[162],"An":[163],"efficient":[164],"updating":[166],"scheme":[167],"also":[169],"used":[170],"avoid":[172],"computationally":[174],"expensive":[175],"singular":[176],"value":[177],"decomposition":[178],"(SVD).":[179],"We":[180],"demonstrate":[181],"performance":[183],"proposed":[186],"both":[189],"synthetic":[190],"real":[192]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}