{"id":"https://openalex.org/W4383503885","doi":"https://doi.org/10.1109/tgrs.2023.3289917","title":"Deep Seismic CS: A Deep Learning Assisted Compressive Sensing for Seismic Data","display_name":"Deep Seismic CS: A Deep Learning Assisted Compressive Sensing for Seismic Data","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4383503885","doi":"https://doi.org/10.1109/tgrs.2023.3289917"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3289917","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3289917","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/A5056812780","display_name":"Naveed Iqbal","orcid":"https://orcid.org/0000-0002-2633-9761"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Naveed Iqbal","raw_affiliation_strings":["Department of Electrical Engineering and the Center for Communication Systems and Sensing, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-2633-9761","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and the Center for Communication Systems and Sensing, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000165797","display_name":"Mudassir Masood","orcid":"https://orcid.org/0000-0003-0462-7874"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mudassir Masood","raw_affiliation_strings":["Department of Electrical Engineering and the Center for Communication Systems and Sensing, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0003-0462-7874","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and the Center for Communication Systems and Sensing, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063764685","display_name":"Motaz Alfarraj","orcid":"https://orcid.org/0000-0002-6052-7221"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Motaz Alfarraj","raw_affiliation_strings":["Department of Electrical Engineering and the SDAIA-KFUPM Joint Research Center for Artificial Intelligence, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-6052-7221","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and the SDAIA-KFUPM Joint Research Center for Artificial Intelligence, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082388493","display_name":"Umair bin Waheed","orcid":"https://orcid.org/0000-0002-5189-0694"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Umair Bin Waheed","raw_affiliation_strings":["Department of Geoscience, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geoscience, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I134085113"],"apc_list":null,"apc_paid":null,"fwci":4.4067,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.9584355,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/geophone","display_name":"Geophone","score":0.9849416017532349},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7201943397521973},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6476021409034729},{"id":"https://openalex.org/keywords/vertical-seismic-profile","display_name":"Vertical seismic profile","score":0.5801311731338501},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4771546721458435},{"id":"https://openalex.org/keywords/terabyte","display_name":"Terabyte","score":0.455073744058609},{"id":"https://openalex.org/keywords/passive-seismic","display_name":"Passive seismic","score":0.4469425678253174},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4408690929412842},{"id":"https://openalex.org/keywords/data-center","display_name":"Data center","score":0.4223422408103943},{"id":"https://openalex.org/keywords/seismology","display_name":"Seismology","score":0.31436657905578613},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.24686619639396667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18902575969696045},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1703406274318695}],"concepts":[{"id":"https://openalex.org/C54187759","wikidata":"https://www.wikidata.org/wiki/Q361564","display_name":"Geophone","level":2,"score":0.9849416017532349},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7201943397521973},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6476021409034729},{"id":"https://openalex.org/C89787772","wikidata":"https://www.wikidata.org/wiki/Q7922855","display_name":"Vertical seismic profile","level":2,"score":0.5801311731338501},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4771546721458435},{"id":"https://openalex.org/C199683683","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Terabyte","level":2,"score":0.455073744058609},{"id":"https://openalex.org/C2780942248","wikidata":"https://www.wikidata.org/wiki/Q1048443","display_name":"Passive seismic","level":2,"score":0.4469425678253174},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4408690929412842},{"id":"https://openalex.org/C153740404","wikidata":"https://www.wikidata.org/wiki/Q671224","display_name":"Data center","level":2,"score":0.4223422408103943},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.31436657905578613},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.24686619639396667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18902575969696045},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1703406274318695},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3289917","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3289917","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":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.5400000214576721}],"awards":[{"id":"https://openalex.org/G129710356","display_name":null,"funder_award_id":"GTEC2013","funder_id":"https://openalex.org/F4320322323","funder_display_name":"King Fahd University of Petroleum and Minerals"}],"funders":[{"id":"https://openalex.org/F4320322323","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1503398984","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1966637115","https://openalex.org/W1971402995","https://openalex.org/W1971971422","https://openalex.org/W1989261702","https://openalex.org/W2034415022","https://openalex.org/W2045748842","https://openalex.org/W2050781067","https://openalex.org/W2103164394","https://openalex.org/W2124662472","https://openalex.org/W2128659236","https://openalex.org/W2129638195","https://openalex.org/W2139446121","https://openalex.org/W2151920332","https://openalex.org/W2164452299","https://openalex.org/W2194775991","https://openalex.org/W2735601242","https://openalex.org/W2792638927","https://openalex.org/W2793348241","https://openalex.org/W2793783688","https://openalex.org/W2907161786","https://openalex.org/W2944761405","https://openalex.org/W2961799636","https://openalex.org/W2963716738","https://openalex.org/W2966617248","https://openalex.org/W2967118492","https://openalex.org/W2967131216","https://openalex.org/W3006380685","https://openalex.org/W3125548729","https://openalex.org/W3128444015","https://openalex.org/W3133856089","https://openalex.org/W3164069575","https://openalex.org/W4234551707","https://openalex.org/W4250955649","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6762364214"],"related_works":["https://openalex.org/W2037807280","https://openalex.org/W2057510257","https://openalex.org/W2091687221","https://openalex.org/W2047926555","https://openalex.org/W2988643590","https://openalex.org/W2120245965","https://openalex.org/W2160855022","https://openalex.org/W2071337536","https://openalex.org/W2318402200","https://openalex.org/W2000647528"],"abstract_inverted_index":{"For":[0],"large-scale":[1],"seismic":[2,47,56,132,204,215],"exploration":[3],"in":[4,119,130,141,268],"areas":[5],"that":[6,152,235],"lack":[7],"even":[8],"basic":[9],"infrastructure,":[10],"wired":[11],"geophones":[12,32,75,90],"are":[13],"impractical":[14],"because":[15],"of":[16,30,34,52,54,65,72,126,150,166,178,214,219,241,249],"the":[17,77,84,99,107,127,131,136,148,158,188,193,202,262],"huge":[18,63],"effort":[19],"involved":[20],"and":[21,25,36,111,224,272,278],"their":[22],"high":[23],"deployment":[24],"operating":[26],"costs.":[27],"A":[28],"network":[29,183,186],"wireless":[31,89],"capable":[33],"recording":[35],"transmitting":[37],"data":[38,57,73,79,96,100,133,140,151,190,254,281],"could":[39,236],"be":[40,155],"an":[41,175],"inexpensive":[42],"solution.":[43],"However,":[44,164],"a":[45,62,91,109,142,179,198,211,233,246,252],"typical":[46],"survey":[48],"can":[49],"generate":[50],"hundreds":[51],"terabytes":[53],"raw":[55],"per":[58],"day.":[59],"It":[60],"takes":[61,124],"amount":[64,71,149],"energy":[66,162],"to":[67,76,88,98,134,138,154],"transmit":[68],"this":[69,120],"massive":[70],"from":[74,86],"on-site":[78],"collection":[80,194],"center,":[81],"thus":[82],"making":[83,160,207],"transformation":[85],"pre-wired":[87],"significant":[92,266],"challenge.":[93],"To":[94],"reduce":[95],"traffic":[97],"center":[101,195],"without":[102,196],"putting":[103],"additional":[104],"strain":[105],"on":[106,251],"geophone,":[108,159],"standalone":[110],"lightweight":[112],"compressive":[113],"sensing":[114,223],"(CS)":[115],"method":[116,123],"is":[117],"proposed":[118,263],"work.":[121],"The":[122,217],"advantage":[125],"inherent":[128],"sparsity":[129],"enable":[135],"geophone":[137],"sense":[139],"compressed":[143,189],"manner.":[144],"This":[145,185],"significantly":[146],"reduces":[147],"needs":[153],"recorded/transmitted":[156],"by":[157],"it":[161,208],"efficient.":[163],"instead":[165],"employing":[167],"conventional":[168],"optimization-based":[169],"CS":[170,220],"reconstruction":[171,231,273],"methods,":[172,261],"we":[173],"propose":[174],"efficient":[176],"implementation":[177],"deep":[180],"convolutional":[181],"neural":[182],"(DCNN).":[184],"processes":[187],"received":[191],"at":[192],"any":[197],"priori":[199],"assumptions":[200],"about":[201],"underlying":[203],"signal":[205],"statistics,":[206],"appropriate":[209],"for":[210,221,230,275],"wide":[212],"range":[213],"data.":[216],"use":[218],"energy-efficient":[222],"transmission":[225],"combined":[226],"with":[227,245,259],"powerful":[228],"DCNN":[229],"yields":[232],"system":[234],"achieve":[237],"signal-to-noise":[238],"ratio":[239],"(SNR)":[240],"around":[242],"30":[243],"dB":[244],"compression":[247,270],"gain":[248,271],"16":[250],"field":[253,280],"set.":[255],"Finally,":[256],"when":[257],"compared":[258],"other":[260],"approach":[264],"demonstrates":[265],"superiority":[267],"maximizing":[269],"quality":[274],"both":[276],"synthetic":[277],"real":[279],"sets.":[282]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
