{"id":"https://openalex.org/W3216263253","doi":"https://doi.org/10.3390/s21237802","title":"Real-Time Stress Level Feedback from Raw Ecg Signals for Personalised, Context-Aware Applications Using Lightweight Convolutional Neural Network Architectures","display_name":"Real-Time Stress Level Feedback from Raw Ecg Signals for Personalised, Context-Aware Applications Using Lightweight Convolutional Neural Network Architectures","publication_year":2021,"publication_date":"2021-11-24","ids":{"openalex":"https://openalex.org/W3216263253","doi":"https://doi.org/10.3390/s21237802","mag":"3216263253","pmid":"https://pubmed.ncbi.nlm.nih.gov/34883806"},"language":"en","primary_location":{"id":"doi:10.3390/s21237802","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21237802","pdf_url":"https://www.mdpi.com/1424-8220/21/23/7802/pdf?version=1637740825","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/1424-8220/21/23/7802/pdf?version=1637740825","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005840944","display_name":"Konstantinos Tzevelekakis","orcid":null},"institutions":[{"id":"https://openalex.org/I4210121775","display_name":"FORTH Institute of Computer Science","ror":"https://ror.org/02tf48g55","country_code":"GR","type":"facility","lineage":["https://openalex.org/I4210121775","https://openalex.org/I8901234"]},{"id":"https://openalex.org/I8901234","display_name":"Foundation for Research and Technology Hellas","ror":"https://ror.org/052rphn09","country_code":"GR","type":"facility","lineage":["https://openalex.org/I8901234"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Konstantinos Tzevelekakis","raw_affiliation_strings":["Foundation for Research and Technology\u2014Hellas (FORTH), Institute of Computer Science, GR-70013 Heraklion, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Foundation for Research and Technology\u2014Hellas (FORTH), Institute of Computer Science, GR-70013 Heraklion, Greece","institution_ids":["https://openalex.org/I4210121775","https://openalex.org/I8901234"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022197014","display_name":"Zinovia Stefanidi","orcid":"https://orcid.org/0000-0001-7317-0009"},"institutions":[{"id":"https://openalex.org/I4210121775","display_name":"FORTH Institute of Computer Science","ror":"https://ror.org/02tf48g55","country_code":"GR","type":"facility","lineage":["https://openalex.org/I4210121775","https://openalex.org/I8901234"]},{"id":"https://openalex.org/I8901234","display_name":"Foundation for Research and Technology Hellas","ror":"https://ror.org/052rphn09","country_code":"GR","type":"facility","lineage":["https://openalex.org/I8901234"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Zinovia Stefanidi","raw_affiliation_strings":["Foundation for Research and Technology\u2014Hellas (FORTH), Institute of Computer Science, GR-70013 Heraklion, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Foundation for Research and Technology\u2014Hellas (FORTH), Institute of Computer Science, GR-70013 Heraklion, Greece","institution_ids":["https://openalex.org/I4210121775","https://openalex.org/I8901234"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038717571","display_name":"George Margetis","orcid":"https://orcid.org/0000-0002-9101-6301"},"institutions":[{"id":"https://openalex.org/I4210121775","display_name":"FORTH Institute of Computer Science","ror":"https://ror.org/02tf48g55","country_code":"GR","type":"facility","lineage":["https://openalex.org/I4210121775","https://openalex.org/I8901234"]},{"id":"https://openalex.org/I8901234","display_name":"Foundation for Research and Technology Hellas","ror":"https://ror.org/052rphn09","country_code":"GR","type":"facility","lineage":["https://openalex.org/I8901234"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"George Margetis","raw_affiliation_strings":["Foundation for Research and Technology\u2014Hellas (FORTH), Institute of Computer Science, GR-70013 Heraklion, Greece"],"raw_orcid":"https://orcid.org/0000-0002-9101-6301","affiliations":[{"raw_affiliation_string":"Foundation for Research and Technology\u2014Hellas (FORTH), Institute of Computer Science, GR-70013 Heraklion, Greece","institution_ids":["https://openalex.org/I4210121775","https://openalex.org/I8901234"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5038717571"],"corresponding_institution_ids":["https://openalex.org/I4210121775","https://openalex.org/I8901234"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":2.0462,"has_fulltext":true,"cited_by_count":33,"citation_normalized_percentile":{"value":0.88675083,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"21","issue":"23","first_page":"7802","last_page":"7802"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7709099054336548},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6970336437225342},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5212196111679077},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4989161491394043},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4888159930706024},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.48013874888420105},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4275127351284027},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3420884609222412}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7709099054336548},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6970336437225342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5212196111679077},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4989161491394043},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4888159930706024},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.48013874888420105},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4275127351284027},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3420884609222412},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D005246","descriptor_name":"Feedback","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005246","descriptor_name":"Feedback","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005246","descriptor_name":"Feedback","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005246","descriptor_name":"Feedback","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012306","descriptor_name":"Risk","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012306","descriptor_name":"Risk","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012306","descriptor_name":"Risk","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012306","descriptor_name":"Risk","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s21237802","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21237802","pdf_url":"https://www.mdpi.com/1424-8220/21/23/7802/pdf?version=1637740825","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:34883806","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34883806","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:doaj.org/article:c18fb82137764b45b08ddee50c5f9ee7","is_oa":true,"landing_page_url":"https://doaj.org/article/c18fb82137764b45b08ddee50c5f9ee7","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 21, Iss 23, p 7802 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/23/7802/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21237802","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 21; Issue 23; Pages: 7802","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8659908","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8659908","pdf_url":null,"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"}],"best_oa_location":{"id":"doi:10.3390/s21237802","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21237802","pdf_url":"https://www.mdpi.com/1424-8220/21/23/7802/pdf?version=1637740825","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":[{"id":"https://metadata.un.org/sdg/16","score":0.8199999928474426,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G83835112","display_name":"Deep AR Law Enforcement Ecosystem","funder_award_id":"883297","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3216263253.pdf","grobid_xml":"https://content.openalex.org/works/W3216263253.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1518433044","https://openalex.org/W1557433409","https://openalex.org/W1912166081","https://openalex.org/W1975183513","https://openalex.org/W1995645776","https://openalex.org/W2001705113","https://openalex.org/W2026891775","https://openalex.org/W2029497408","https://openalex.org/W2031590924","https://openalex.org/W2042324951","https://openalex.org/W2056523469","https://openalex.org/W2059995600","https://openalex.org/W2093001406","https://openalex.org/W2097431774","https://openalex.org/W2143624594","https://openalex.org/W2162800060","https://openalex.org/W2168482461","https://openalex.org/W2171801645","https://openalex.org/W2218733455","https://openalex.org/W2316698880","https://openalex.org/W2484954437","https://openalex.org/W2589100236","https://openalex.org/W2782694740","https://openalex.org/W2785419426","https://openalex.org/W2809242972","https://openalex.org/W2894771803","https://openalex.org/W2936978234","https://openalex.org/W2941146140","https://openalex.org/W2954948187","https://openalex.org/W2957344258","https://openalex.org/W2980089758","https://openalex.org/W2996057901","https://openalex.org/W3003257820","https://openalex.org/W3010462844","https://openalex.org/W3024816874","https://openalex.org/W3034126796","https://openalex.org/W3037294239","https://openalex.org/W3046919919","https://openalex.org/W3082016297","https://openalex.org/W3100777112","https://openalex.org/W3103145119","https://openalex.org/W3145728983","https://openalex.org/W3167394498","https://openalex.org/W3172915759","https://openalex.org/W3188589000","https://openalex.org/W3210819471","https://openalex.org/W4226444298","https://openalex.org/W6661173690"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W4380075502"],"abstract_inverted_index":{"Human":[0],"stress":[1,49,106,136,143,194,235],"is":[2,63,156,174],"intricately":[3],"linked":[4],"with":[5,159],"mental":[6],"processes":[7],"such":[8,40,201],"as":[9,202],"decision":[10],"making.":[11],"Public":[12],"protection":[13],"practitioners,":[14],"including":[15],"Law":[16],"Enforcement":[17],"Agents":[18],"(LEAs),":[19],"are":[20,45],"forced":[21],"to":[22,42,64,176],"make":[23],"difficult":[24],"decisions":[25],"during":[26],"high-pressure":[27],"operations,":[28],"under":[29],"strenuous":[30],"circumstances.":[31],"In":[32,126],"this":[33,127],"respect,":[34],"systems":[35],"and":[36,56,67,91,138,158,171,206,233,247],"applications":[37],"that":[38,59],"assist":[39],"practitioners":[41],"take":[43],"decisions,":[44],"increasingly":[46],"incorporating":[47],"user":[48],"level":[50,70],"information":[51],"for":[52,78,85,121,134,165],"their":[53],"development,":[54],"adaptation,":[55],"evaluation.":[57],"To":[58],"end,":[60],"our":[61],"goal":[62],"accurately":[65],"detect":[66],"classify":[68],"the":[69,79,103,112,135,172,190,220,223,231,239],"of":[71,81,105,124,245],"acute,":[72],"short-term":[73,148],"stress,":[74],"in":[75,92,102,167],"real":[76],"time,":[77],"development":[80],"personalized,":[82],"context-aware":[83],"solutions":[84],"LEAs.":[86],"Deep":[87],"Neural":[88,95],"Networks":[89,96],"(DNNs),":[90],"particular":[93],"Convolutional":[94],"(CNNs),":[97],"have":[98,116],"been":[99,118],"gaining":[100],"traction":[101],"field":[104],"analysis,":[107],"exhibiting":[108],"promising":[109],"results.":[110],"Furthermore,":[111],"electrocardiogram":[113],"(ECG)":[114],"signals,":[115],"also":[117],"widely":[119],"adopted":[120],"estimating":[122],"levels":[123],"stress.":[125],"work,":[128],"we":[129],"propose":[130],"two":[131,191],"CNN":[132],"architectures":[133],"detection":[137],"3-level":[139],"(low,":[140],"moderate,":[141],"high)":[142],"classification":[144,195,236],"tasks,":[145],"using":[146,209,217,238],"ultra":[147],"raw":[149],"ECG":[150],"signals":[151],"(3":[152],"s).":[153],"One":[154],"architecture":[155],"simple":[157],"a":[160,210],"low":[161],"memory":[162],"footprint,":[163],"suitable":[164],"running":[166],"wearable":[168],"edge-computing":[169],"nodes,":[170],"other":[173],"able":[175],"learn":[177],"more":[178,182],"complex":[179],"features,":[180],"having":[181],"trainable":[183],"parameters.":[184],"The":[185],"models":[186],"were":[187],"trained":[188],"on":[189,222,230],"publicly":[192],"available":[193],"datasets,":[196],"after":[197],"applying":[198],"pre-processing":[199],"techniques,":[200],"data":[203,207],"pruning,":[204],"down-sampling,":[205],"augmentation,":[208],"sliding":[211],"window":[212],"approach.":[213],"After":[214],"hyperparameter":[215],"tuning,":[216],"4-fold":[218],"cross-validation,":[219],"evaluation":[221],"test":[224],"set":[225],"demonstrated":[226],"state-of-the-art":[227],"accuracy":[228,244],"both":[229],"3-":[232],"2-level":[234],"task":[237],"DriveDB":[240],"dataset,":[241],"reporting":[242],"an":[243],"83.55%":[246],"98.77%":[248],"respectively.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}