{"id":"https://openalex.org/W4402352177","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650728","title":"Low-Pass Filter Application for Anomaly Detection with Sparse Autoencoder","display_name":"Low-Pass Filter Application for Anomaly Detection with Sparse Autoencoder","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352177","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650728"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650728","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078944541","display_name":"Maira Farias Andrade Lira","orcid":"https://orcid.org/0000-0002-3839-9681"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Maira Farias Andrade Lira","raw_affiliation_strings":["Universidade Federal de Pernambuco,Centro de Informática,Recife,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal de Pernambuco,Centro de Informática,Recife,Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107079560","display_name":"Elias Amancio Siqueira-Filho","orcid":null},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Elias Amancio Siqueira-Filho","raw_affiliation_strings":["Universidade Federal de Pernambuco,Centro de Informática,Recife,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal de Pernambuco,Centro de Informática,Recife,Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083998049","display_name":"Ricardo B. C. Prud\u00eancio","orcid":"https://orcid.org/0000-0001-7084-1233"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ricardo Prudencio","raw_affiliation_strings":["Universidade Federal de Pernambuco,Centro de Informática,Recife,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal de Pernambuco,Centro de Informática,Recife,Brazil","institution_ids":["https://openalex.org/I25112270"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5078944541"],"corresponding_institution_ids":["https://openalex.org/I25112270"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12901644,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"89","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9987999796867371,"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.9847000241279602,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8697773218154907},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6030731201171875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5730289220809937},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5003612041473389},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48921632766723633},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.47317153215408325},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.27414295077323914},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.10044723749160767}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8697773218154907},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6030731201171875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5730289220809937},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5003612041473389},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48921632766723633},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.47317153215408325},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.27414295077323914},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.10044723749160767}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650728","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1565746575","https://openalex.org/W2122646361","https://openalex.org/W2479027570","https://openalex.org/W3017317785","https://openalex.org/W3040204705","https://openalex.org/W3040266635","https://openalex.org/W3135550350","https://openalex.org/W4200252498","https://openalex.org/W4206422821","https://openalex.org/W4212967226","https://openalex.org/W4214900601","https://openalex.org/W4312433903","https://openalex.org/W6700456436","https://openalex.org/W6745109666","https://openalex.org/W6801012654","https://openalex.org/W6802669405","https://openalex.org/W6808786000","https://openalex.org/W6847523634","https://openalex.org/W6847669299"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W3186512740","https://openalex.org/W3194885736","https://openalex.org/W4220775285","https://openalex.org/W4363671829","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,52],"(AD)":[2],"techniques":[3,44],"are":[4],"adopted":[5,148],"to":[6,71,136,235,242,252],"identify":[7],"instances":[8],"with":[9],"patterns":[10],"that":[11,91,111,226],"significantly":[12],"differ":[13],"from":[14],"the":[15,34,40,51,84,98,104,129,138,156,159,170,177,182,202,207,215,229],"general":[16,228],"behavior":[17],"of":[18,23,42,53,100,119,131,158,193,231,238],"a":[19,80,116,143,190,196],"dataset.":[20],"The":[21,185],"development":[22],"new":[24],"techniques,":[25],"such":[26,48],"as":[27,49,74],"those":[28],"based":[29,78],"on":[30,79,169,176,189,206],"deep":[31],"learning,":[32],"and":[33,108,173],"higher":[35],"data":[36],"availability":[37],"have":[38],"increased":[39],"use":[41,130,230],"AD":[43,60,183,194,247],"in":[45,50,55,95,103,122,134,195,227,246],"challenging":[46],"tasks":[47],"failures":[54],"industrial":[56],"equipment\u2019s.":[57],"Generally,":[58,201],"an":[59,63],"technique":[61],"generates":[62],"anomaly":[64,105,139,171,208],"score":[65,106,209],"for":[66,114,149],"each":[67],"instance,":[68],"later":[69],"used":[70],"classify":[72],"it":[73],"anomalous":[75],"or":[76],"normal,":[77],"threshold":[81],"above":[82],"which":[83],"instance":[85],"is":[86,92,97],"considered":[87],"anomalous.":[88],"A":[89],"problem":[90],"commonly":[93],"observed":[94,225],"practice":[96],"presence":[99],"spurious":[101],"peaks":[102],"signal":[107,179],"other":[109],"irregularities":[110],"may":[112],"cause,":[113],"example,":[115],"high":[117],"number":[118],"false":[120,221],"positives":[121],"AD.":[123,150],"In":[124,151,213],"this":[125],"paper,":[126],"we":[127,154],"investigated":[128,155],"low-pass":[132,160,244],"filters":[133,161,245],"order":[135],"smooth":[137],"scores":[140],"derived":[141],"by":[142,181],"Sparse":[144],"Autoencoder":[145],"(SAE)":[146],"model":[147],"our":[152],"experiments,":[153],"usefulness":[157],"considering":[162],"two":[163],"different":[164],"approaches:":[165],"(1)":[166],"directly":[167,205],"applied":[168,175,204,217],"scores;":[172],"(2)":[174],"classification":[178,219],"returned":[180],"model.":[184],"experiments":[186],"were":[187],"performed":[188],"case":[191],"study":[192],"metro\u2019s":[197],"air":[198],"production":[199],"unit.":[200],"filter":[203,216],"maximized":[210],"true":[211],"positives.":[212,222],"turn,":[214],"after":[218],"minimized":[220],"It":[223],"was":[224,233],"LPF":[232],"essential":[234],"detect":[236],"sequences":[237],"anomalies.":[239],"Thus,":[240],"how":[241],"apply":[243],"must":[248],"be":[249],"defined":[250],"according":[251],"specific":[253],"application":[254],"goals.":[255]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}