{"id":"https://openalex.org/W4322731402","doi":"https://doi.org/10.1109/access.2023.3247947","title":"A Bayesian Deep Learning Approach With Convolutional Feature Engineering to Discriminate Cyber-Physical Intrusions in Smart Grid Systems","display_name":"A Bayesian Deep Learning Approach With Convolutional Feature Engineering to Discriminate Cyber-Physical Intrusions in Smart Grid Systems","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4322731402","doi":"https://doi.org/10.1109/access.2023.3247947"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3247947","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3247947","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10050022.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10050022.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103128237","display_name":"Devinder Kaur","orcid":"https://orcid.org/0000-0002-9337-5068"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Devinder Kaur","raw_affiliation_strings":["School of Engineering, Deakin University, Geelong, VIC, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Deakin University, Geelong, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Adnan Anwar","orcid":"https://orcid.org/0000-0003-0070-182X"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Adnan Anwar","raw_affiliation_strings":["Centre for Cyber Security Research and Innovation (CSRI), School of Information Technology, Deakin University, Geelong, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0003-0070-182X","affiliations":[{"raw_affiliation_string":"Centre for Cyber Security Research and Innovation (CSRI), School of Information Technology, Deakin University, Geelong, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004948235","display_name":"Innocent Kamwa","orcid":"https://orcid.org/0000-0002-3568-3716"},"institutions":[{"id":"https://openalex.org/I43406934","display_name":"Universit\u00e9 Laval","ror":"https://ror.org/04sjchr03","country_code":"CA","type":"education","lineage":["https://openalex.org/I43406934"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Innocent Kamwa","raw_affiliation_strings":["Department of Electrical Engineering and Computer Engineering, Laval University, Quebec City, Canada"],"raw_orcid":"https://orcid.org/0000-0002-3568-3716","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Engineering, Laval University, Quebec City, Canada","institution_ids":["https://openalex.org/I43406934"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007829488","display_name":"Shama Naz Islam","orcid":"https://orcid.org/0000-0002-2354-7960"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shama Islam","raw_affiliation_strings":["School of Engineering, Deakin University, Geelong, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-2354-7960","affiliations":[{"raw_affiliation_string":"School of Engineering, Deakin University, Geelong, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028098322","display_name":"S. M. Muyeen","orcid":"https://orcid.org/0000-0003-4955-6889"},"institutions":[{"id":"https://openalex.org/I60342839","display_name":"Qatar University","ror":"https://ror.org/00yhnba62","country_code":"QA","type":"education","lineage":["https://openalex.org/I60342839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"S. M. Muyeen","raw_affiliation_strings":["Department of Electrical Engineering, Qatar University, Doha, Qatar"],"raw_orcid":"https://orcid.org/0000-0003-4955-6889","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Qatar University, Doha, Qatar","institution_ids":["https://openalex.org/I60342839"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067867890","display_name":"Nasser Hosseinzadeh","orcid":"https://orcid.org/0000-0002-8755-1176"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Nasser Hosseinzadeh","raw_affiliation_strings":["School of Engineering, Deakin University, Geelong, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-8755-1176","affiliations":[{"raw_affiliation_string":"School of Engineering, Deakin University, Geelong, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.821,"has_fulltext":true,"cited_by_count":36,"citation_normalized_percentile":{"value":0.95517706,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"11","issue":null,"first_page":"18910","last_page":"18920"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10917","display_name":"Smart Grid Security and Resilience","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7554622888565063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7084245681762695},{"id":"https://openalex.org/keywords/smart-grid","display_name":"Smart grid","score":0.6305973529815674},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6013932824134827},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5882260799407959},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5776424407958984},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.5657778978347778},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5563487410545349},{"id":"https://openalex.org/keywords/cyber-physical-system","display_name":"Cyber-physical system","score":0.5531944036483765},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4465988874435425},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.44284167885780334},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4307031035423279},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35977065563201904},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10296308994293213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7554622888565063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7084245681762695},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.6305973529815674},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6013932824134827},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5882260799407959},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5776424407958984},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.5657778978347778},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5563487410545349},{"id":"https://openalex.org/C179768478","wikidata":"https://www.wikidata.org/wiki/Q1120057","display_name":"Cyber-physical system","level":2,"score":0.5531944036483765},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4465988874435425},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.44284167885780334},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4307031035423279},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35977065563201904},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10296308994293213},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/access.2023.3247947","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3247947","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10050022.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:qspace.qu.edu.qa:10576/61937","is_oa":true,"landing_page_url":"http://hdl.handle.net/10576/61937","pdf_url":"http://qspace.qu.edu.qa/bitstream/10576/61937/1/A_Bayesian_Deep_Learning_Approach_With_Convolutional_Feature_Engineering_to_Discriminate_Cyber-Physical_Intrusions_in_Smart_Grid_Systems.pdf","source":{"id":"https://openalex.org/S4306400014","display_name":"Qatar University QSpace (Qatar University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I60342839","host_organization_name":"Qatar University","host_organization_lineage":["https://openalex.org/I60342839"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:29375062c86a46ee8d3b16c205acf85e","is_oa":true,"landing_page_url":"https://doaj.org/article/29375062c86a46ee8d3b16c205acf85e","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":"IEEE Access, Vol 11, Pp 18910-18920 (2023)","raw_type":"article"},{"id":"pmh:oai:figshare.com:article/22329490","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/A_Bayesian_Deep_Learning_Approach_With_Convolutional_Feature_Engineering_to_Discriminate_Cyber-Physical_Intrusions_in_Smart_Grid_Systems/22329490","pdf_url":null,"source":{"id":"https://openalex.org/S4306402621","display_name":"INDIGO (University of Illinois at Chicago)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39422238","host_organization_name":"University of Illinois Chicago","host_organization_lineage":["https://openalex.org/I39422238"],"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":"","raw_type":"Text"},{"id":"pmh:oai:figshare.com:article/25204196","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/A_Bayesian_Deep_Learning_Approach_With_Convolutional_Feature_Engineering_to_Discriminate_Cyber-Physical_Intrusions_in_Smart_Grid_Systems/25204196","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3247947","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3247947","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10050022.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6399999856948853}],"awards":[{"id":"https://openalex.org/G3534789799","display_name":null,"funder_award_id":"ALLRP 567550-21","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G8494166278","display_name":null,"funder_award_id":"ALLRP 567550\u201421","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320310137","display_name":"Universit\u00e9 Laval","ror":"https://ror.org/04sjchr03"},{"id":"https://openalex.org/F4320320970","display_name":"Deakin University","ror":"https://ror.org/02czsnj07"},{"id":"https://openalex.org/F4320334468","display_name":"Qatar National Library","ror":"https://ror.org/02jv93662"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"},{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4322731402.pdf","grobid_xml":"https://content.openalex.org/works/W4322731402.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W1969911795","https://openalex.org/W1977555035","https://openalex.org/W2086540457","https://openalex.org/W2097654008","https://openalex.org/W2117646649","https://openalex.org/W2119290091","https://openalex.org/W2154663898","https://openalex.org/W2336386743","https://openalex.org/W2399941526","https://openalex.org/W2531448500","https://openalex.org/W2775103799","https://openalex.org/W2786918196","https://openalex.org/W2907351452","https://openalex.org/W2907763162","https://openalex.org/W2911981000","https://openalex.org/W2936809465","https://openalex.org/W2953049129","https://openalex.org/W2960616960","https://openalex.org/W2962851448","https://openalex.org/W2979829384","https://openalex.org/W2990536252","https://openalex.org/W2999772819","https://openalex.org/W3004036452","https://openalex.org/W3020265068","https://openalex.org/W3032021129","https://openalex.org/W3041293089","https://openalex.org/W3082065751","https://openalex.org/W3102477513","https://openalex.org/W3120934607","https://openalex.org/W3139317474","https://openalex.org/W3172554013","https://openalex.org/W3182952669","https://openalex.org/W3186690272","https://openalex.org/W3204527343","https://openalex.org/W3216390247","https://openalex.org/W4295788744","https://openalex.org/W4311415873","https://openalex.org/W4318718442","https://openalex.org/W6600247753","https://openalex.org/W6792254717","https://openalex.org/W6849321538"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W3021430260","https://openalex.org/W2968586400","https://openalex.org/W2942650110","https://openalex.org/W4281986673"],"abstract_inverted_index":{"The":[0,106],"emergence":[1],"of":[2],"cyber-physical":[3,78],"smart":[4],"grid":[5,13],"(CPSG)":[6],"systems":[7,115,160],"has":[8,34],"revolutionized":[9],"the":[10,16,31,40,45,49,71,81,85,96,102,119,137,145,150],"traditional":[11],"power":[12],"by":[14],"enabling":[15],"bidirectional":[17],"energy":[18],"flow":[19],"between":[20,30],"consumers":[21],"and":[22,51,87,131,169],"utilities.":[23],"However,":[24],"due":[25],"to":[26,39,76,94,101,155],"escalated":[27],"information":[28],"exchange":[29],"end-users,":[32],"it":[33,140],"posed":[35],"a":[36,60],"greater":[37],"challenge":[38],"cyber":[41,50],"security":[42],"mechanisms":[43],"for":[44],"communication":[46],"networks":[47,68,129],"at":[48],"physical":[52],"planes.":[53],"To":[54],"address":[55],"these":[56],"challenges,":[57],"we":[58],"propose":[59],"Bayesian":[61,72],"approach":[62],"integrated":[63],"with":[64],"deep":[65,121],"convolutional":[66],"neural":[67,128],"(CNN-Bayesian).":[69],"While,":[70],"component":[73],"is":[74,109],"used":[75],"discriminate":[77,156],"intrusions":[79,103,157],"from":[80],"normal":[82],"events":[83],"in":[84,158],"binary":[86],"multi-class":[88],"events.":[89],"CNN":[90],"layers":[91],"are":[92],"utilized":[93],"handle":[95],"high-dimensional":[97],"feature":[98],"space":[99],"prior":[100],"classification":[104,123,153],"task.":[105],"proposed":[107,146],"method":[108,148],"validated":[110],"using":[111,161],"real-time":[112],"Industrial":[113],"control":[114],"(ICS)":[116],"dataset":[117],"against":[118],"standard":[120],"learning-based":[122],"methods":[124,154],"such":[125,164],"as":[126,165],"recurrent":[127],"(RNN)":[130],"long-short":[132],"term":[133],"memory":[134],"(LSTM).":[135],"From":[136],"experimental":[138],"results,":[139],"can":[141],"be":[142],"inferred":[143],"that":[144],"CNN-Bayesian":[147],"outperforms":[149],"existing":[151],"benchmark":[152],"CPSG":[159],"evaluation":[162],"metrics":[163],"accuracy,":[166],"precision,":[167],"recall,":[168],"<inline-formula":[170],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[171],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[172],"<tex-math":[173],"notation=\"LaTeX\">$F1$":[174],"</tex-math></inline-formula>":[175],"-score.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":7}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}