{"id":"https://openalex.org/W3033548601","doi":"https://doi.org/10.1109/tifs.2020.3036242","title":"Long Short-Term Memory With Gate and State Level Fusion for Light Field-Based Face Recognition","display_name":"Long Short-Term Memory With Gate and State Level Fusion for Light Field-Based Face Recognition","publication_year":2020,"publication_date":"2020-11-05","ids":{"openalex":"https://openalex.org/W3033548601","doi":"https://doi.org/10.1109/tifs.2020.3036242","mag":"3033548601"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2020.3036242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2020.3036242","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Information Forensics and Security","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1905.04421","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088311682","display_name":"Alireza Sepas\u2010Moghaddam","orcid":"https://orcid.org/0000-0002-4881-5386"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alireza Sepas-Moghaddam","raw_affiliation_strings":["Queen\u2019s University, Kingston, ON, Canada","[Department of Electrical, and Computer Engineering, Queen's University, Kingston, ON, Canada]"],"raw_orcid":"https://orcid.org/0000-0002-4881-5386","affiliations":[{"raw_affiliation_string":"Queen\u2019s University, Kingston, ON, Canada","institution_ids":["https://openalex.org/I204722609"]},{"raw_affiliation_string":"[Department of Electrical, and Computer Engineering, Queen's University, Kingston, ON, Canada]","institution_ids":["https://openalex.org/I204722609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039812985","display_name":"Ali Etemad","orcid":"https://orcid.org/0000-0001-7128-0220"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ali Etemad","raw_affiliation_strings":["Queen\u2019s University, Kingston, ON, Canada","[Department of Electrical, and Computer Engineering, Queen's University, Kingston, ON, Canada]"],"raw_orcid":"https://orcid.org/0000-0001-7128-0220","affiliations":[{"raw_affiliation_string":"Queen\u2019s University, Kingston, ON, Canada","institution_ids":["https://openalex.org/I204722609"]},{"raw_affiliation_string":"[Department of Electrical, and Computer Engineering, Queen's University, Kingston, ON, Canada]","institution_ids":["https://openalex.org/I204722609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044708805","display_name":"Fernando Pereira","orcid":"https://orcid.org/0000-0001-6100-947X"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]},{"id":"https://openalex.org/I4210120471","display_name":"Instituto de Telecomunica\u00e7\u00f5es","ror":"https://ror.org/02ht4fk33","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210120471"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Fernando Pereira","raw_affiliation_strings":["Instituto de Telecomunica\u00e7 oes, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Lisbon, Portugal"],"raw_orcid":"https://orcid.org/0000-0001-6100-947X","affiliations":[{"raw_affiliation_string":"Instituto de Telecomunica\u00e7 oes, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103","https://openalex.org/I4210120471"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019322980","display_name":"Paulo Lobato Correia","orcid":"https://orcid.org/0000-0001-6525-9572"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]},{"id":"https://openalex.org/I4210120471","display_name":"Instituto de Telecomunica\u00e7\u00f5es","ror":"https://ror.org/02ht4fk33","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210120471"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Paulo Lobato Correia","raw_affiliation_strings":["Instituto de Telecomunica\u00e7 oes, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Lisbon, Portugal"],"raw_orcid":"https://orcid.org/0000-0001-6525-9572","affiliations":[{"raw_affiliation_string":"Instituto de Telecomunica\u00e7 oes, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103","https://openalex.org/I4210120471"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1923,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47927434,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"16","issue":null,"first_page":"1365","last_page":"1379"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9994000196456909,"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/T11448","display_name":"Face recognition and analysis","score":0.9994000196456909,"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/T10057","display_name":"Face and Expression Recognition","score":0.9983999729156494,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9983999729156494,"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":0.8256522417068481},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6542487144470215},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6532947421073914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6325331330299377},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6229650378227234},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5804309844970703},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5468140244483948},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5217010378837585},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.48684781789779663},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.48091670870780945},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4628405272960663},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.44879499077796936},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4247227907180786},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4243730902671814},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4020284414291382},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3488745391368866},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.07906776666641235}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8256522417068481},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6542487144470215},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6532947421073914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6325331330299377},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6229650378227234},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5804309844970703},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5468140244483948},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5217010378837585},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.48684781789779663},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.48091670870780945},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4628405272960663},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.44879499077796936},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4247227907180786},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4243730902671814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4020284414291382},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3488745391368866},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.07906776666641235},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tifs.2020.3036242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2020.3036242","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Information Forensics and Security","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1905.04421","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.04421","pdf_url":"https://arxiv.org/pdf/1905.04421","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3033548601","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1905.04421v2","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1905.04421","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1905.04421","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1905.04421","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.04421","pdf_url":"https://arxiv.org/pdf/1905.04421","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3033548601.pdf","grobid_xml":"https://content.openalex.org/works/W3033548601.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W276045419","https://openalex.org/W1598796236","https://openalex.org/W1689711448","https://openalex.org/W1964479141","https://openalex.org/W2028880308","https://openalex.org/W2049862374","https://openalex.org/W2054781681","https://openalex.org/W2055747889","https://openalex.org/W2063366997","https://openalex.org/W2064675550","https://openalex.org/W2069143585","https://openalex.org/W2073942619","https://openalex.org/W2076063813","https://openalex.org/W2079735306","https://openalex.org/W2098693229","https://openalex.org/W2100649405","https://openalex.org/W2105557003","https://openalex.org/W2115733720","https://openalex.org/W2118463056","https://openalex.org/W2136461127","https://openalex.org/W2137313943","https://openalex.org/W2141200867","https://openalex.org/W2150355110","https://openalex.org/W2163808566","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2292885564","https://openalex.org/W2294985758","https://openalex.org/W2325939864","https://openalex.org/W2402144811","https://openalex.org/W2508429489","https://openalex.org/W2522485430","https://openalex.org/W2546875627","https://openalex.org/W2565516711","https://openalex.org/W2613569861","https://openalex.org/W2716916105","https://openalex.org/W2752782242","https://openalex.org/W2753630964","https://openalex.org/W2756315940","https://openalex.org/W2769581371","https://openalex.org/W2782072221","https://openalex.org/W2792324968","https://openalex.org/W2792396704","https://openalex.org/W2884739346","https://openalex.org/W2885653416","https://openalex.org/W2890499605","https://openalex.org/W2919115771","https://openalex.org/W2922220370","https://openalex.org/W2942331158","https://openalex.org/W2952387868","https://openalex.org/W2962958286","https://openalex.org/W2963420686","https://openalex.org/W2963602021","https://openalex.org/W2963839617","https://openalex.org/W2996033780","https://openalex.org/W3015476328","https://openalex.org/W6610021723","https://openalex.org/W6635679246","https://openalex.org/W6675783809","https://openalex.org/W6680152570","https://openalex.org/W6713134421","https://openalex.org/W6761941605"],"related_works":["https://openalex.org/W3096199586","https://openalex.org/W3158854271","https://openalex.org/W3010094765","https://openalex.org/W2951819117","https://openalex.org/W3168378981","https://openalex.org/W2939146114","https://openalex.org/W3142292783","https://openalex.org/W2963447094","https://openalex.org/W2801271919","https://openalex.org/W2898065209","https://openalex.org/W2952467144","https://openalex.org/W3175333894","https://openalex.org/W2769504394","https://openalex.org/W2898126708","https://openalex.org/W2765621372","https://openalex.org/W2339652278","https://openalex.org/W3166020125","https://openalex.org/W2909624725","https://openalex.org/W2945695009","https://openalex.org/W2926527602"],"abstract_inverted_index":{"Long":[0],"Short-Term":[1],"Memory":[2],"(LSTM)":[3],"is":[4,127],"a":[5,43,158],"prominent":[6],"recurrent":[7],"neural":[8],"network":[9],"for":[10,26,116,136,193],"extracting":[11],"dependencies":[12],"from":[13,49,103,167,215],"sequential":[14],"data":[15,61],"such":[16],"as":[17,38],"time-series":[18],"and":[19,112,153],"multi-view":[20],"data,":[21],"having":[22],"achieved":[23],"impressive":[24],"results":[25,203],"different":[27],"visual":[28],"recognition":[29,117,138,195],"tasks.":[30,118],"A":[31,170],"conventional":[32],"LSTM":[33,39,66,94,124,190],"network,":[34,40],"hereafter":[35],"referred":[36],"only":[37,69],"can":[41],"learn":[42,102,149],"model":[44],"to":[45,100,109,162],"posteriorly":[46],"extract":[47],"information":[48,79,166],"one":[50],"input":[51,217],"sequence.":[52],"However,":[53],"if":[54],"two":[55,92],"or":[56],"more":[57,113],"dependent":[58],"sequences":[59,72,105],"of":[60,77,121,186,208],"are":[62,98],"simultaneously":[63,106],"acquired,":[64,107],"the":[65,78,122,150,174,184,188,197,205,209],"networks":[67],"may":[68],"process":[70],"those":[71],"consecutively,":[73],"not":[74],"taking":[75],"benefit":[76],"carried":[80],"out":[81],"by":[82,129],"their":[83],"mutual":[84],"dependencies.":[85],"In":[86],"this":[87,89],"context,":[88],"paper":[90],"proposes":[91],"novel":[93,123,189,210],"cell":[95,125,146,191,211],"architectures":[96,126,147,192,212],"that":[97],"able":[99],"jointly":[101,148],"multiple":[104],"targeting":[108],"create":[110],"richer":[111,164],"effective":[114],"models":[115],"The":[119,144],"efficacy":[120],"assessed":[128],"integrating":[130],"them":[131],"into":[132],"deep":[133],"learning-based":[134],"methods":[135],"face":[137,194],"with":[139,173],"multi-view,":[140],"light":[141,159,199],"field":[142,160],"images.":[143],"new":[145],"scene":[151],"horizontal":[152],"vertical":[154],"parallaxes":[155],"available":[156],"in":[157],"image,":[161],"capture":[163],"spatio-angular":[165],"both":[168],"directions.":[169],"comprehensive":[171],"evaluation,":[172],"IST-EURECOM":[175],"LFFD":[176],"dataset":[177],"using":[178,187],"three":[179],"challenging":[180],"evaluation":[181],"protocols,":[182],"shows":[183],"advantage":[185],"over":[196],"state-of-the-art":[198],"field-based":[200],"methods.":[201],"These":[202],"highlight":[204],"added":[206],"value":[207],"when":[213],"learning":[214],"correlated":[216],"sequences.":[218]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}