{"id":"https://openalex.org/W3193836690","doi":null,"title":"Cognitive GPR for subsurface sensing based on edge computing and deep reinforcement learning","display_name":"Cognitive GPR for subsurface sensing based on edge computing and deep reinforcement learning","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3193836690","mag":"3193836690"},"language":"en","primary_location":{"id":"pmh:oai:scholar.utc.edu:theses-1894","doi":null,"is_oa":true,"landing_page_url":"https://scholar.utc.edu/theses/728","pdf_url":"https://scholar.utc.edu/cgi/viewcontent.cgi?article=1894&context=theses","source":{"id":"https://openalex.org/S4377196682","display_name":"UTC Scholar (University of Tennessee at Chattanooga)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I177097968","host_organization_name":"University of Tennessee at Chattanooga","host_organization_lineage":["https://openalex.org/I177097968"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Masters Theses and Doctoral Dissertations","raw_type":"text"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://scholar.utc.edu/cgi/viewcontent.cgi?article=1894&context=theses","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040631627","display_name":"Maxwell M. Omwenga","orcid":"https://orcid.org/0000-0003-4408-8326","observed_orcids":["https://orcid.org/0000-0003-4408-8326"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Maxwell M. Omwenga","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4408-8326","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5040631627"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.9994999766349792,"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9994999766349792,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":9.999999747378752e-05,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/subsurface-sensing","display_name":"subsurface sensing","score":0.8429999947547913},{"id":"https://openalex.org/keywords/edge-computing","display_name":"edge computing","score":0.8700000047683716},{"id":"https://openalex.org/keywords/deep-reinforcement-learning","display_name":"deep reinforcement learning","score":0.9520000219345093},{"id":"https://openalex.org/keywords/deep-q-learning","display_name":"deep Q-learning","score":0.824999988079071},{"id":"https://openalex.org/keywords/ddpg","display_name":"deep deterministic policy gradient","score":0.9700000286102295},{"id":"https://openalex.org/keywords/reward-function-design","display_name":"reward function design","score":0.7490000128746033},{"id":"https://openalex.org/keywords/subsurface-target-detection","display_name":"subsurface object detection","score":0.9210000038146973},{"id":"https://openalex.org/keywords/sequential-decision-processes","display_name":"sequential decision processes","score":0.7490000128746033}],"concepts":[{"id":"https://openalex.org/C71813955","wikidata":"https://www.wikidata.org/wiki/Q503560","display_name":"Ground-penetrating radar","level":3,"score":0.7732812166213989},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5992485880851746},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5547439455986023},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.4937988221645355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4235556125640869},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3349878787994385},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.26783397793769836},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.23079019784927368},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.09680163860321045},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0909523069858551},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:scholar.utc.edu:theses-1894","doi":null,"is_oa":true,"landing_page_url":"https://scholar.utc.edu/theses/728","pdf_url":"https://scholar.utc.edu/cgi/viewcontent.cgi?article=1894&context=theses","source":{"id":"https://openalex.org/S4377196682","display_name":"UTC Scholar (University of Tennessee at Chattanooga)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I177097968","host_organization_name":"University of Tennessee at Chattanooga","host_organization_lineage":["https://openalex.org/I177097968"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Masters Theses and Doctoral Dissertations","raw_type":"text"},{"id":"mag:3193836690","doi":null,"is_oa":false,"landing_page_url":"https://scholar.utc.edu/cgi/viewcontent.cgi?article=1894&context=theses","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:scholar.utc.edu:theses-1894","doi":null,"is_oa":true,"landing_page_url":"https://scholar.utc.edu/theses/728","pdf_url":"https://scholar.utc.edu/cgi/viewcontent.cgi?article=1894&context=theses","source":{"id":"https://openalex.org/S4377196682","display_name":"UTC Scholar (University of Tennessee at Chattanooga)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I177097968","host_organization_name":"University of Tennessee at Chattanooga","host_organization_lineage":["https://openalex.org/I177097968"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Masters Theses and Doctoral Dissertations","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4943999946117401}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3193836690.pdf","grobid_xml":"https://content.openalex.org/works/W3193836690.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W596928057","https://openalex.org/W1504000887","https://openalex.org/W1582934392","https://openalex.org/W1594275308","https://openalex.org/W1601081659","https://openalex.org/W1932624639","https://openalex.org/W1971471853","https://openalex.org/W1995875735","https://openalex.org/W2003030056","https://openalex.org/W2022758041","https://openalex.org/W2039866862","https://openalex.org/W2063146632","https://openalex.org/W2071010831","https://openalex.org/W2099834208","https://openalex.org/W2121863487","https://openalex.org/W2133059825","https://openalex.org/W2134166966","https://openalex.org/W2143368986","https://openalex.org/W2155027007","https://openalex.org/W2155411643","https://openalex.org/W2158501196","https://openalex.org/W2165150801","https://openalex.org/W2227909145","https://openalex.org/W2344423009","https://openalex.org/W2472333518","https://openalex.org/W2552949552","https://openalex.org/W2569644762","https://openalex.org/W2575705757","https://openalex.org/W2582616844","https://openalex.org/W2594788700","https://openalex.org/W2607185608","https://openalex.org/W2626044724","https://openalex.org/W2761545465","https://openalex.org/W2766631298","https://openalex.org/W2781786131","https://openalex.org/W2783999187","https://openalex.org/W2786787998","https://openalex.org/W2790587404","https://openalex.org/W2890227524","https://openalex.org/W2904483377","https://openalex.org/W2907503094","https://openalex.org/W2944190409","https://openalex.org/W2958437053","https://openalex.org/W2965337314","https://openalex.org/W2966477753","https://openalex.org/W2979897999","https://openalex.org/W2982681137","https://openalex.org/W3028024295","https://openalex.org/W3129491111","https://openalex.org/W3186886679"],"related_works":["https://openalex.org/W3132156451","https://openalex.org/W6980129304","https://openalex.org/W3215915255","https://openalex.org/W4226229936","https://openalex.org/W3134010413","https://openalex.org/W3119622082","https://openalex.org/W4392517680","https://openalex.org/W4404758118","https://openalex.org/W3155003861","https://openalex.org/W3091398351"],"abstract_inverted_index":{"Ground":[0],"penetrating":[1],"radars":[2],"(GPRs)":[3],"have":[4],"been":[5],"extensively":[6],"used":[7],"in":[8,41,236],"many":[9],"industrial":[10],"applications,":[11],"such":[12],"as":[13,102],"coal":[14],"mining,":[15],"structural":[16],"health":[17],"monitoring,":[18],"subsurface":[19,56,140,160],"utilities":[20],"detection":[21,142,239],"and":[22,24,117,149,219,243],"localization,":[23],"autonomous":[25,65],"driving.":[26],"Most":[27],"of":[28,48,94,139,146,159,238],"the":[29,37,46,54,132,137,144],"existing":[30],"GPR":[31,50,66,110,174,184,209,217,234],"systems":[32,235],"are":[33,214],"human-operated":[34],"due":[35],"to":[36,62,154,172],"need":[38],"for":[39,83,131],"experience":[40],"operation":[42,93],"configurations":[43],"based":[44,86,111,187],"on":[45,87,112,188],"interpretation":[47],"collected":[49],"data.":[51,210],"To":[52],"achieve":[53],"best":[55],"sensing":[57,74],"performance,":[58],"it":[59],"is":[60,90,100,122,129,170,185],"desired":[61],"design":[63],"an":[64,189],"system":[67],"that":[68,227],"can":[69],"operate":[70],"adaptively":[71],"under":[72,97],"varying":[73],"conditions.":[75],"In":[76],"this":[77,98],"research,":[78],"first,":[79],"a":[80,103,108,156,202],"generic":[81],"architecture":[82,99],"cognitive":[84,95,109,183,230],"GPRs":[85,96,231],"edge":[88],"computing":[89],"studied.":[91],"The":[92,211],"formulated":[101],"sequential":[104],"decision":[105],"process.":[106],"Then":[107],"2D":[113,166],"B-Scan":[114,167],"image":[115,168],"analysis":[116,169,176],"deep":[118,191,196],"Q-learning":[119],"network":[120],"(DQN)":[121],"investigated.":[123],"A":[124,180],"novel":[125],"entropy-based":[126],"reward":[127,204],"function":[128,205],"designed":[130],"DQN":[133],"model":[134],"by":[135],"using":[136,216],"results":[138,225],"object":[141,244],"(via":[143,151],"region":[145],"interest":[147],"identification)":[148],"recognition":[150],"classification).":[152],"Furthermore,":[153],"acquire":[155],"global":[157],"view":[158],"objects":[161],"with":[162,201],"complex":[163],"shape":[164],"configurations,":[165],"extended":[171],"3D":[173,208],"data":[175],"termed":[177],"\u201cScan":[178],"Cloud.\u201d":[179],"scan":[181],"cloud-enabled":[182],"studied":[186],"advanced":[190],"reinforcement":[192],"learning":[193],"method":[194],"called":[195,222],"deterministic":[197],"policy":[198],"gradient":[199],"(DDPG)":[200],"new":[203],"derived":[206],"from":[207],"proposed":[212,229],"methods":[213],"evaluated":[215],"modeling":[218],"simulation":[220],"software":[221],"GprMax.":[223],"Simulation":[224],"show":[226],"our":[228],"outperform":[232],"other":[233],"terms":[237],"accuracy,":[240],"operating":[241],"time,":[242],"reconstruction.":[245]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2021-08-30T00:00:00"}
