{"id":"https://openalex.org/W1974924261","doi":"https://doi.org/10.1121/1.1862592","title":"Time-reversal imaging for classification of submerged elastic targets via Gibbs sampling and the Relevance Vector Machine","display_name":"Time-reversal imaging for classification of submerged elastic targets via Gibbs sampling and the Relevance Vector Machine","publication_year":2005,"publication_date":"2005-04-01","ids":{"openalex":"https://openalex.org/W1974924261","doi":"https://doi.org/10.1121/1.1862592","mag":"1974924261","pmid":"https://pubmed.ncbi.nlm.nih.gov/15898643"},"language":"en","primary_location":{"id":"doi:10.1121/1.1862592","doi":"https://doi.org/10.1121/1.1862592","is_oa":false,"landing_page_url":"https://doi.org/10.1121/1.1862592","pdf_url":null,"source":{"id":"https://openalex.org/S11296630","display_name":"The Journal of the Acoustical Society of America","issn_l":"0001-4966","issn":["0001-4966","1520-8524","1520-9024"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-b","cwts-core","dongbi-b","erih-plus","jufo-3","ki-jl-1","medline","norway-2","poland-100","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320226","host_organization_name":"Acoustical Society of America","host_organization_lineage":["https://openalex.org/P4310320226"],"host_organization_lineage_names":["Acoustical Society of America"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of the Acoustical Society of America","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Nilanjan Dasgupta","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nilanjan Dasgupta","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina\u200927708-0291"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina\u200927708-0291","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016448581","display_name":"Lawrence Carin","orcid":"https://orcid.org/0000-0001-6277-7948","observed_orcids":["https://orcid.org/0000-0001-6277-7948"]},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lawrence Carin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina\u200927708-0291"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina\u200927708-0291","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170897317"],"apc_list":null,"apc_paid":null,"fwci":1.6,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.79065506,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"117","issue":"4","first_page":"1999","last_page":"2011"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"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/T11698","display_name":"Underwater Acoustics Research","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.00279999990016222,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.0013000000035390258,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/time-reversal-imaging","display_name":"time-reversal imaging","score":0.9950000047683716},{"id":"https://openalex.org/keywords/channel-parameter-estimation","display_name":"channel parameter estimation","score":0.6970000267028809},{"id":"https://openalex.org/keywords/geoacoustic-inversion","display_name":"geoacoustic inversion","score":0.9599999785423279},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.9950000047683716},{"id":"https://openalex.org/keywords/relevance-vector-machine","display_name":"relevance vector machine","score":0.9350000023841858},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"feature extraction","score":0.5429999828338623},{"id":"https://openalex.org/keywords/channel-mismatch","display_name":"channel mismatch","score":0.7260000109672546},{"id":"https://openalex.org/keywords/matched-field-processing","display_name":"matched field processing","score":0.7429999709129333}],"concepts":[{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.649860143661499},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6403414011001587},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5813392996788025},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5596327185630798},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.5358105301856995},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5255842804908752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4917784035205841},{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.4703619182109833},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4620494246482849},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.44781988859176636},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33220335841178894},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2342991828918457},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16935089230537415},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.12909626960754395},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.1133686900138855},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.09020644426345825},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07096511125564575},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1121/1.1862592","doi":"https://doi.org/10.1121/1.1862592","is_oa":false,"landing_page_url":"https://doi.org/10.1121/1.1862592","pdf_url":null,"source":{"id":"https://openalex.org/S11296630","display_name":"The Journal of the Acoustical Society of America","issn_l":"0001-4966","issn":["0001-4966","1520-8524","1520-9024"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-b","cwts-core","dongbi-b","erih-plus","jufo-3","ki-jl-1","medline","norway-2","poland-100","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320226","host_organization_name":"Acoustical Society of America","host_organization_lineage":["https://openalex.org/P4310320226"],"host_organization_lineage_names":["Acoustical Society of America"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of the Acoustical Society of America","raw_type":"journal-article"},{"id":"pmid:15898643","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/15898643","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of the Acoustical Society of America","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1973220693","https://openalex.org/W1974126856","https://openalex.org/W1994785670","https://openalex.org/W2009915717","https://openalex.org/W2012834708","https://openalex.org/W2017549801","https://openalex.org/W2020639671","https://openalex.org/W2022477534","https://openalex.org/W2024345710","https://openalex.org/W2029356337","https://openalex.org/W2044751415","https://openalex.org/W2052018164","https://openalex.org/W2056113181","https://openalex.org/W2056760934","https://openalex.org/W2056969652","https://openalex.org/W2068333739","https://openalex.org/W2070285821","https://openalex.org/W2088092393","https://openalex.org/W2092595081","https://openalex.org/W2106407685","https://openalex.org/W2107138442","https://openalex.org/W2109100930","https://openalex.org/W2110200678","https://openalex.org/W2110398209","https://openalex.org/W2149755721","https://openalex.org/W2151283225","https://openalex.org/W2154728678","https://openalex.org/W2180153954","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2112870863","https://openalex.org/W2134584866","https://openalex.org/W1963747336","https://openalex.org/W2024345710","https://openalex.org/W2273814856","https://openalex.org/W1981188053","https://openalex.org/W2167267675","https://openalex.org/W2072327333","https://openalex.org/W3004615625","https://openalex.org/W2092868191"],"abstract_inverted_index":{"Time-reversal":[0,25,86],"imaging":[1,50],"(TRI)":[2],"is":[3,10,15,41,51,110,124,137,164],"analogous":[4],"to":[5,23,29,36,43,82,101,115,166,170],"matched-field":[6],"processing,":[7],"although":[8],"TRI":[9,182],"typically":[11],"very":[12],"wideband":[13],"and":[14,181,190],"appropriate":[16],"for":[17],"subsequent":[18,116],"target":[19,31,117,191],"classification":[20,120,162,192],"(in":[21],"addition":[22,100],"localization).":[24],"techniques,":[26],"as":[27],"applied":[28,114],"acoustic":[30],"classification,":[32],"are":[33,56,79,183],"highly":[34],"sensitive":[35],"channel":[37,46,77,156,173],"mismatch.":[38],"Hence,":[39],"it":[40],"crucial":[42],"estimate":[44,74],"the":[45,76,107,127,135,160,171,187,194],"parameters":[47,78],"before":[48],"time-reversal":[49,84],"performed.":[52],"The":[53,69,119,132,175],"channel-parameter":[54],"statistics":[55],"estimated":[57],"here":[58,94],"by":[59,95,126,144],"applying":[60],"a":[61,71,89,96,145,155],"geoacoustic":[62],"inversion":[63],"technique":[64,136],"based":[65],"on":[66,139],"Gibbs":[67,179],"sampling.":[68],"maximum":[70],"posteriori":[72],"(MAP)":[73],"of":[75,104,121,134,178],"then":[80],"used":[81],"perform":[83],"imaging.":[85],"implementation":[87],"requires":[88],"fast":[90],"forward":[91],"model,":[92,158],"implemented":[93],"normal-mode":[97],"framework.":[98],"In":[99],"imaging,":[102],"extraction":[103,189],"features":[105],"from":[106],"time-reversed":[108,122],"images":[109],"explored,":[111],"with":[112,154,186],"these":[113],"classification.":[118],"signatures":[123],"performed":[125],"relevance":[128],"vector":[129],"machine":[130],"(RVM).":[131],"efficacy":[133],"analyzed":[138],"simulated":[140],"in-channel":[141],"data":[142],"generated":[143],"free-field":[146],"finite":[147],"element":[148],"method":[149],"(FEM)":[150],"code,":[151],"in":[152],"conjunction":[153],"propagation":[157],"wherein":[159],"final":[161],"performance":[163],"demonstrated":[165],"be":[167],"relatively":[168],"insensitive":[169],"associated":[172],"parameters.":[174],"underlying":[176],"theory":[177],"sampling":[180],"presented":[184],"along":[185],"feature":[188],"via":[193],"RVM.":[195]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2016-06-24T00:00:00"}