{"id":"https://openalex.org/W4386030128","doi":"https://doi.org/10.3390/s23167284","title":"Time-Distributed Framework for 3D Reconstruction Integrating Fringe Projection with Deep Learning","display_name":"Time-Distributed Framework for 3D Reconstruction Integrating Fringe Projection with Deep Learning","publication_year":2023,"publication_date":"2023-08-20","ids":{"openalex":"https://openalex.org/W4386030128","doi":"https://doi.org/10.3390/s23167284","pmid":"https://pubmed.ncbi.nlm.nih.gov/37631820"},"language":"en","primary_location":{"id":"doi:10.3390/s23167284","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23167284","pdf_url":"https://www.mdpi.com/1424-8220/23/16/7284/pdf?version=1692591224","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/16/7284/pdf?version=1692591224","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089282845","display_name":"Hieu Nguyen","orcid":"https://orcid.org/0000-0002-5154-0125"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I1327069482","display_name":"National Institute on Drug Abuse","ror":"https://ror.org/00fq5cm18","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I1327069482"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew-Hieu Nguyen","raw_affiliation_strings":["Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD 21224, USA"],"raw_orcid":"https://orcid.org/0000-0002-5154-0125","affiliations":[{"raw_affiliation_string":"Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD 21224, USA","institution_ids":["https://openalex.org/I1327069482","https://openalex.org/I1299303238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100356536","display_name":"Zhaoyang Wang","orcid":"https://orcid.org/0000-0002-6384-3107"},"institutions":[{"id":"https://openalex.org/I168959743","display_name":"University of America","ror":"https://ror.org/03s0c9350","country_code":"US","type":"education","lineage":["https://openalex.org/I168959743"]},{"id":"https://openalex.org/I84470341","display_name":"Catholic University of America","ror":"https://ror.org/047yk3s18","country_code":"US","type":"education","lineage":["https://openalex.org/I84470341"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhaoyang Wang","raw_affiliation_strings":["Department of Mechanical Engineering, The Catholic University of America, Washington, DC 20064, USA"],"raw_orcid":"https://orcid.org/0000-0002-6384-3107","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, The Catholic University of America, Washington, DC 20064, USA","institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100356536"],"corresponding_institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.683,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.71551286,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"23","issue":"16","first_page":"7284","last_page":"7284"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.7064430117607117},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6907950043678284},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6246026158332825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6144771575927734},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.6107187271118164},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.538726806640625},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5212748050689697},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5076030492782593},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.47458672523498535},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.4661622643470764},{"id":"https://openalex.org/keywords/structured-light","display_name":"Structured light","score":0.42218703031539917},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35713452100753784},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3213449716567993},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3201102316379547},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2961803078651428}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7064430117607117},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6907950043678284},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6246026158332825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6144771575927734},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.6107187271118164},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.538726806640625},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5212748050689697},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5076030492782593},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.47458672523498535},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.4661622643470764},{"id":"https://openalex.org/C193581530","wikidata":"https://www.wikidata.org/wiki/Q683778","display_name":"Structured light","level":2,"score":0.42218703031539917},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35713452100753784},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3213449716567993},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3201102316379547},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2961803078651428},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s23167284","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23167284","pdf_url":"https://www.mdpi.com/1424-8220/23/16/7284/pdf?version=1692591224","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:37631820","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37631820","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,"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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10458373","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10458373","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10458373/pdf/sensors-23-07284.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:8fba72f7bbc54818881c90267616289c","is_oa":true,"landing_page_url":"https://doaj.org/article/8fba72f7bbc54818881c90267616289c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 23, Iss 16, p 7284 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/16/7284/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23167284","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 23; Issue 16; Pages: 7284","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23167284","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23167284","pdf_url":"https://www.mdpi.com/1424-8220/23/16/7284/pdf?version=1692591224","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4386030128.pdf"},"referenced_works_count":84,"referenced_works":["https://openalex.org/W1505191356","https://openalex.org/W1901129140","https://openalex.org/W1967139035","https://openalex.org/W1978366855","https://openalex.org/W1990613440","https://openalex.org/W2006943762","https://openalex.org/W2028362538","https://openalex.org/W2037061351","https://openalex.org/W2038571930","https://openalex.org/W2051754112","https://openalex.org/W2053917166","https://openalex.org/W2055467580","https://openalex.org/W2092873805","https://openalex.org/W2094262626","https://openalex.org/W2134731454","https://openalex.org/W2145595389","https://openalex.org/W2157274504","https://openalex.org/W2171646521","https://openalex.org/W2221221697","https://openalex.org/W2434421859","https://openalex.org/W2602764693","https://openalex.org/W2610272310","https://openalex.org/W2767566744","https://openalex.org/W2791731233","https://openalex.org/W2792775903","https://openalex.org/W2902206865","https://openalex.org/W2919115771","https://openalex.org/W2923997689","https://openalex.org/W2942723599","https://openalex.org/W2945770468","https://openalex.org/W2948097639","https://openalex.org/W2963926543","https://openalex.org/W2971914169","https://openalex.org/W2972609628","https://openalex.org/W2985276643","https://openalex.org/W2990026901","https://openalex.org/W2990295915","https://openalex.org/W3006260981","https://openalex.org/W3007268491","https://openalex.org/W3009405738","https://openalex.org/W3025800305","https://openalex.org/W3037848181","https://openalex.org/W3038484145","https://openalex.org/W3040491826","https://openalex.org/W3083158743","https://openalex.org/W3087588036","https://openalex.org/W3091350737","https://openalex.org/W3099860820","https://openalex.org/W3107327644","https://openalex.org/W3130399606","https://openalex.org/W3137638783","https://openalex.org/W3155339433","https://openalex.org/W3161292253","https://openalex.org/W3161606058","https://openalex.org/W3172610252","https://openalex.org/W3175345191","https://openalex.org/W3185836578","https://openalex.org/W3206595850","https://openalex.org/W4200001586","https://openalex.org/W4200351482","https://openalex.org/W4205333018","https://openalex.org/W4205962726","https://openalex.org/W4210323025","https://openalex.org/W4210787840","https://openalex.org/W4225364179","https://openalex.org/W4288052519","https://openalex.org/W4291415233","https://openalex.org/W4293661073","https://openalex.org/W4295949366","https://openalex.org/W4308202654","https://openalex.org/W4308730191","https://openalex.org/W4312755042","https://openalex.org/W4313541731","https://openalex.org/W4318336240","https://openalex.org/W4318478351","https://openalex.org/W4318562111","https://openalex.org/W4321381456","https://openalex.org/W4322588526","https://openalex.org/W4327852052","https://openalex.org/W4327909727","https://openalex.org/W4363672709","https://openalex.org/W4366834062","https://openalex.org/W4367302269","https://openalex.org/W4367310869"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W2909431601","https://openalex.org/W2997655528"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"integrating":[3],"structured":[4],"light":[5],"with":[6,116],"deep":[7,53],"learning":[8],"has":[9],"gained":[10],"considerable":[11],"attention":[12],"in":[13,35],"three-dimensional":[14],"(3D)":[15],"shape":[16,50],"reconstruction":[17,51,101,111],"due":[18],"to":[19,65,92,136],"its":[20],"high":[21],"precision":[22],"and":[23,62,75,97,123,161],"suitability":[24],"for":[25,46,151,158],"dynamic":[26],"applications.":[27,163],"While":[28],"previous":[29],"techniques":[30],"primarily":[31],"focus":[32],"on":[33],"processing":[34],"the":[36,78,99,108,117,127,141],"spatial":[37],"domain,":[38],"this":[39],"paper":[40],"proposes":[41],"a":[42,85,147],"novel":[43],"time-distributed":[44,63,109],"approach":[45,57],"temporal":[47,68,87],"structured-light":[48,88],"3D":[49,100,110],"using":[52],"learning.":[54],"The":[55],"proposed":[56,142],"utilizes":[58],"an":[59],"autoencoder":[60],"network":[61,150],"wrapper":[64],"convert":[66],"multiple":[67,152],"fringe":[69],"patterns":[70],"into":[71],"their":[72],"corresponding":[73],"numerators":[74],"denominators":[76],"of":[77,146],"arctangent":[79],"functions.":[80],"Fringe":[81],"projection":[82],"profilometry":[83],"(FPP),":[84],"well-known":[86],"technique,":[89],"is":[90],"employed":[91],"prepare":[93],"high-quality":[94],"ground":[95],"truth":[96],"depict":[98],"process.":[102],"Our":[103],"experimental":[104],"findings":[105],"show":[106],"that":[107],"technique":[112],"achieves":[113],"comparable":[114],"outcomes":[115],"dual-frequency":[118],"dataset":[119,129],"(p":[120,130],"=":[121,131],"0.014)":[122],"higher":[124],"accuracy":[125],"than":[126],"triple-frequency":[128],"1.029":[132],"\u00d7":[133],"10-9),":[134],"according":[135],"non-parametric":[137],"statistical":[138],"tests.":[139],"Moreover,":[140],"approach's":[143],"straightforward":[144],"implementation":[145],"single":[148],"training":[149],"converters":[153],"makes":[154],"it":[155],"more":[156],"practical":[157],"scientific":[159],"research":[160],"industrial":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
