{"id":"https://openalex.org/W4316468870","doi":"https://doi.org/10.3390/s23020988","title":"Hierarchical Image Transformation and Multi-Level Features for Anomaly Defect Detection","display_name":"Hierarchical Image Transformation and Multi-Level Features for Anomaly Defect Detection","publication_year":2023,"publication_date":"2023-01-15","ids":{"openalex":"https://openalex.org/W4316468870","doi":"https://doi.org/10.3390/s23020988","pmid":"https://pubmed.ncbi.nlm.nih.gov/36679785"},"language":"en","primary_location":{"id":"doi:10.3390/s23020988","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23020988","pdf_url":"https://www.mdpi.com/1424-8220/23/2/988/pdf?version=1674111282","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/1424-8220/23/2/988/pdf?version=1674111282","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050605490","display_name":"Isack Farady","orcid":"https://orcid.org/0000-0003-1160-8890"},"institutions":[{"id":"https://openalex.org/I177671886","display_name":"Mercu Buana University","ror":"https://ror.org/00qjgk605","country_code":"ID","type":"education","lineage":["https://openalex.org/I177671886"]},{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["ID","TW"],"is_corresponding":false,"raw_author_name":"Isack Farady","raw_affiliation_strings":["Department of Electrical Engineering, Mercu Buana University, Jakarta 11650, Indonesia","Department of Electrical and Communication Engineering, Yuan Ze University, Taoyuan 320, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Mercu Buana University, Jakarta 11650, Indonesia","institution_ids":["https://openalex.org/I177671886"]},{"raw_affiliation_string":"Department of Electrical and Communication Engineering, Yuan Ze University, Taoyuan 320, Taiwan","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023453353","display_name":"Chia-Chen Kuo","orcid":"https://orcid.org/0000-0002-7672-377X"},"institutions":[{"id":"https://openalex.org/I4210107525","display_name":"National Center for High-Performance Computing","ror":"https://ror.org/01jpzd518","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210107525","https://openalex.org/I4210128167","https://openalex.org/I4210166867"]},{"id":"https://openalex.org/I4210166867","display_name":"National Institutes of Applied Research","ror":"https://ror.org/05wcstg80","country_code":"TW","type":"government","lineage":["https://openalex.org/I4210128167","https://openalex.org/I4210166867"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chia-Chen Kuo","raw_affiliation_strings":["National Center for High-Performance Computing, National Applied Research Laboratories, Hsinchu 300, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Center for High-Performance Computing, National Applied Research Laboratories, Hsinchu 300, Taiwan","institution_ids":["https://openalex.org/I4210166867","https://openalex.org/I4210107525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009152648","display_name":"Hui\u2010Fuang Ng","orcid":"https://orcid.org/0000-0003-4394-2770"},"institutions":[{"id":"https://openalex.org/I931681460","display_name":"Universiti Tunku Abdul Rahman","ror":"https://ror.org/050pq4m56","country_code":"MY","type":"education","lineage":["https://openalex.org/I931681460"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Hui-Fuang Ng","raw_affiliation_strings":["Department of Computer Science, University Tunku Abdul Rahman, Kampar 31900, Malaysia"],"raw_orcid":"https://orcid.org/0000-0003-4394-2770","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University Tunku Abdul Rahman, Kampar 31900, Malaysia","institution_ids":["https://openalex.org/I931681460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087964642","display_name":"Chih\u2010Yang Lin","orcid":"https://orcid.org/0000-0002-0401-8473"},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Chih-Yang Lin","raw_affiliation_strings":["Department of Electrical and Communication Engineering, Yuan Ze University, Taoyuan 320, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-0401-8473","affiliations":[{"raw_affiliation_string":"Department of Electrical and Communication Engineering, Yuan Ze University, Taoyuan 320, Taiwan","institution_ids":["https://openalex.org/I99908691"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5087964642"],"corresponding_institution_ids":["https://openalex.org/I99908691"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":2.1538,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.89514877,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"23","issue":"2","first_page":"988","last_page":"988"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.991599977016449,"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/T11515","display_name":"Bacillus and Francisella bacterial research","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7125110030174255},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.708852231502533},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.7057634592056274},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6989855766296387},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5808408856391907},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5430365204811096},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4602336883544922},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4538811147212982},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.43454355001449585},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4256875514984131},{"id":"https://openalex.org/keywords/ideal","display_name":"Ideal (ethics)","score":0.41873592138290405},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.41802045702934265},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41680917143821716},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.41339388489723206},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32408225536346436}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7125110030174255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.708852231502533},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.7057634592056274},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6989855766296387},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5808408856391907},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5430365204811096},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4602336883544922},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4538811147212982},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.43454355001449585},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4256875514984131},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.41873592138290405},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41802045702934265},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41680917143821716},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.41339388489723206},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32408225536346436},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s23020988","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23020988","pdf_url":"https://www.mdpi.com/1424-8220/23/2/988/pdf?version=1674111282","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:36679785","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36679785","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:pubmedcentral.nih.gov:9861680","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9861680","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"},{"id":"pmh:oai:doaj.org/article:c58f9641b3ae4375a5c38b90d15e3889","is_oa":true,"landing_page_url":"https://doaj.org/article/c58f9641b3ae4375a5c38b90d15e3889","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 23, Iss 2, p 988 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/2/988/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23020988","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 23; Issue 2; Pages: 988","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23020988","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23020988","pdf_url":"https://www.mdpi.com/1424-8220/23/2/988/pdf?version=1674111282","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":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5400000214576721}],"awards":[{"id":"https://openalex.org/G1106719449","display_name":null,"funder_award_id":"MOST 111-2221-E-155-039-MY3","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G1758253551","display_name":null,"funder_award_id":"-2221-E-155","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G4143951077","display_name":null,"funder_award_id":"110-2221-E-155-039-MY3","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G4871424909","display_name":null,"funder_award_id":"MOST 110-2221-E-155-039-MY3","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4316468870.pdf"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W1992699253","https://openalex.org/W1996118086","https://openalex.org/W2019524107","https://openalex.org/W2038819732","https://openalex.org/W2089554624","https://openalex.org/W2108598243","https://openalex.org/W2118020555","https://openalex.org/W2122646361","https://openalex.org/W2132870739","https://openalex.org/W2152010828","https://openalex.org/W2171604933","https://openalex.org/W2194775991","https://openalex.org/W2278186031","https://openalex.org/W2533835508","https://openalex.org/W2599354622","https://openalex.org/W2611650229","https://openalex.org/W2740930567","https://openalex.org/W2756489700","https://openalex.org/W2772723798","https://openalex.org/W2783748519","https://openalex.org/W2784032999","https://openalex.org/W2790344751","https://openalex.org/W2791103947","https://openalex.org/W2803255133","https://openalex.org/W2803674491","https://openalex.org/W2901866350","https://openalex.org/W2914570111","https://openalex.org/W2948982773","https://openalex.org/W2963049059","https://openalex.org/W2999575747","https://openalex.org/W3016757214","https://openalex.org/W3035983404","https://openalex.org/W3040266635","https://openalex.org/W3086419524","https://openalex.org/W3096831136","https://openalex.org/W3101156210","https://openalex.org/W3105939760","https://openalex.org/W3106848223","https://openalex.org/W3120891664","https://openalex.org/W3143975418","https://openalex.org/W3147184966","https://openalex.org/W3159879667","https://openalex.org/W3160366495","https://openalex.org/W3184778778","https://openalex.org/W3195516695","https://openalex.org/W4200152289","https://openalex.org/W4205388843","https://openalex.org/W4239510810","https://openalex.org/W4308235797","https://openalex.org/W6605096470","https://openalex.org/W6679349572","https://openalex.org/W6683199847","https://openalex.org/W6685488477","https://openalex.org/W6751494907","https://openalex.org/W6751866786","https://openalex.org/W6780027702","https://openalex.org/W6948268659"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"Anomalies":[0],"are":[1],"a":[2,25,60,72,89,138,156,181],"set":[3],"of":[4,13,16,29,51,152,164],"samples":[5,166],"that":[6,98,167,192,202],"do":[7],"not":[8,67],"follow":[9],"the":[10,14,63,107,148,169,174,187,210],"normal":[11],"behavior":[12],"majority":[15],"data.":[17,110],"In":[18,84],"an":[19,77,122],"industrial":[20,102,214],"dataset,":[21],"anomalies":[22,188],"appear":[23,100],"in":[24,39,101,132,176],"very":[26],"small":[27],"number":[28],"samples.":[30],"Currently,":[31],"deep":[32],"learning-based":[33],"models":[34],"have":[35],"achieved":[36],"important":[37],"advances":[38],"image":[40,142],"anomaly":[41,123],"detection.":[42],"However,":[43],"with":[44],"general":[45],"models,":[46],"real-world":[47],"application":[48],"data":[49,191],"consisting":[50],"non-ideal":[52,96,170],"images,":[53,58],"also":[54],"known":[55],"as":[56],"poison":[57,94],"become":[59],"challenge.":[61],"When":[62],"work":[64],"environment":[65],"is":[66,82],"conducive":[68],"to":[69,92,126,128,185],"consistently":[70],"acquiring":[71],"good":[73],"or":[74,95],"ideal":[75],"sample,":[76],"additional":[78],"adaptive":[79],"learning":[80],"model":[81,160,184],"needed.":[83],"this":[85],"work,":[86],"we":[87],"design":[88],"potential":[90],"methodology":[91],"tackle":[93],"images":[97],"commonly":[99],"production":[103],"lines":[104],"by":[105],"enhancing":[106],"existing":[108],"training":[109,165],"We":[111],"propose":[112],"Hierarchical":[113],"Image":[114],"Transformation":[115],"and":[116,146,172,205],"Multi-level":[117],"Features":[118],"(HIT-MiLF)":[119],"modules":[120],"for":[121,141],"detection":[124],"network":[125],"adapt":[127],"perturbances":[129],"from":[130,155,189],"novelties":[131],"testing":[133],"images.":[134],"This":[135],"approach":[136],"provides":[137],"hierarchical":[139,203],"process":[140],"transformation":[143,204],"during":[144],"pre-processing":[145],"explores":[147],"most":[149],"efficient":[150],"layer":[151],"extracted":[153],"features":[154,178],"CNN":[157],"backbone.":[158],"The":[159],"generates":[161],"new":[162,190],"transformations":[163],"simulate":[168],"condition":[171],"learn":[173],"normality":[175],"high-dimensional":[177],"before":[179],"applying":[180],"Gaussian":[182],"mixture":[183],"detect":[186],"it":[193],"has":[194],"never":[195],"seen":[196],"before.":[197],"Our":[198],"experimental":[199],"results":[200],"show":[201],"multi-level":[206],"feature":[207],"exploration":[208],"improve":[209],"baseline":[211],"performance":[212],"on":[213],"metal":[215],"datasets.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}