{"id":"https://openalex.org/W4293253177","doi":"https://doi.org/10.1109/iccad55197.2022.9853881","title":"Cross-Domain Anomaly Detection using Unsupervised Representation Learning and Domain Adaption","display_name":"Cross-Domain Anomaly Detection using Unsupervised Representation Learning and Domain Adaption","publication_year":2022,"publication_date":"2022-07-13","ids":{"openalex":"https://openalex.org/W4293253177","doi":"https://doi.org/10.1109/iccad55197.2022.9853881"},"language":"en","primary_location":{"id":"doi:10.1109/iccad55197.2022.9853881","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad55197.2022.9853881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Control, Automation and Diagnosis (ICCAD)","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/A5085166264","display_name":"ZhiLei Shao","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"ZhiLei Shao","raw_affiliation_strings":["Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,P. R. China","Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, P. R. China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,P. R. China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, P. R. China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048504571","display_name":"Huailiang Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"HuaiLiang Zheng","raw_affiliation_strings":["Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,P. R. China","Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, P. R. China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,P. R. China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, P. R. China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064391626","display_name":"XueQian Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"XueQian Wang","raw_affiliation_strings":["Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,P. R. China","Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, P. R. China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,P. R. China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, P. R. China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013703026","display_name":"Bin Liang","orcid":"https://orcid.org/0000-0001-9131-5478"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Liang","raw_affiliation_strings":["Tsinghua University Tsinghua University,Department of Automation,Beijing,P. R. China","Department of Automation, Tsinghua University Tsinghua University, Beijing, P. R. China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University Tsinghua University,Department of Automation,Beijing,P. R. China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University Tsinghua University, Beijing, P. R. China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5085166264"],"corresponding_institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08573254,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980999827384949,"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":0.9980999827384949,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9692000150680542,"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.9369000196456909,"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/computer-science","display_name":"Computer science","score":0.7677616477012634},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7536433935165405},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6972402334213257},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6390249133110046},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6108323335647583},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.6081514358520508},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5622074604034424},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5387071371078491},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5330815315246582},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4992256164550781},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.48284631967544556},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.383093923330307},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33311668038368225},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10941377282142639},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.0941709578037262}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7677616477012634},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7536433935165405},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6972402334213257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6390249133110046},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6108323335647583},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.6081514358520508},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5622074604034424},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5387071371078491},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5330815315246582},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4992256164550781},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.48284631967544556},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.383093923330307},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33311668038368225},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10941377282142639},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0941709578037262},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccad55197.2022.9853881","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad55197.2022.9853881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Control, Automation and Diagnosis (ICCAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4312246223","https://openalex.org/W4285233543","https://openalex.org/W3119773509","https://openalex.org/W3208297503","https://openalex.org/W2889153461","https://openalex.org/W3174759195","https://openalex.org/W2964117661","https://openalex.org/W4230838436","https://openalex.org/W4388405611","https://openalex.org/W2619127353"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,17,20,48,51,72,75,100],"urgent":[3],"demands":[4],"of":[5,19,22,71],"industrial":[6],"fault":[7],"detection,":[8],"cross-domain":[9,29],"detection":[10,31,90,110],"is":[11,66,78,86],"a":[12,28],"promising":[13],"strategy":[14],"for":[15,67,79],"overcoming":[16],"obstacle":[18],"premise":[21],"data":[23,73],"identical-distribution.":[24],"This":[25],"paper":[26],"proposes":[27],"anomaly":[30],"method":[32,85,102],"based":[33],"on":[34],"unsupervised":[35],"representation":[36],"learning":[37],"and":[38,55,74,94],"domain":[39],"adaptation.":[40],"In":[41],"order":[42],"to":[43],"learn":[44],"effective":[45],"features":[46],"from":[47],"original":[49],"signals,":[50],"multidimensional":[52],"scale":[53],"loss":[54,60],"an":[56],"improved":[57],"instance-based":[58],"discriminative":[59],"are":[61],"combined.":[62],"The":[63,83],"first":[64],"one":[65,77],"retaining":[68],"structural":[69],"information":[70],"second":[76],"obtaining":[80],"domain-invariant":[81],"characteristic.":[82],"proposed":[84,101],"validated":[87],"in":[88],"two":[89],"cases":[91],"including":[92],"manipulator":[93],"bearing.":[95],"Detection":[96],"results":[97],"show":[98],"that":[99],"has":[103],"superior":[104],"performance":[105],"than":[106],"several":[107],"widely":[108],"used":[109],"methods.":[111]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}