{"id":"https://openalex.org/W4400056070","doi":"https://doi.org/10.1049/cvi2.12297","title":"DualAD: Dual adversarial network for image anomaly detection\u22c6","display_name":"DualAD: Dual adversarial network for image anomaly detection\u22c6","publication_year":2024,"publication_date":"2024-06-25","ids":{"openalex":"https://openalex.org/W4400056070","doi":"https://doi.org/10.1049/cvi2.12297"},"language":"en","primary_location":{"id":"doi:10.1049/cvi2.12297","is_oa":true,"landing_page_url":"https://doi.org/10.1049/cvi2.12297","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cvi2.12297","source":{"id":"https://openalex.org/S166929102","display_name":"IET Computer Vision","issn_l":"1751-9632","issn":["1751-9632","1751-9640"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Computer Vision","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cvi2.12297","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111240116","display_name":"Yonghao Wan","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonghao Wan","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics  Nanjing China","Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics  Nanjing China","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018817476","display_name":"Aimin Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Aimin Feng","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics  Nanjing China","Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics  Nanjing China","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5018817476"],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":{"value":2000,"currency":"EUR","value_usd":2200},"apc_paid":{"value":2000,"currency":"EUR","value_usd":2200},"fwci":0.7724,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74801197,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"18","issue":"8","first_page":"1138","last_page":"1148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9922000169754028,"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/T11515","display_name":"Bacillus and Francisella bacterial research","score":0.9854000210762024,"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/anomaly-detection","display_name":"Anomaly detection","score":0.730177104473114},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7126255035400391},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6931988000869751},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5901749730110168},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5561208724975586},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.513461172580719},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.48058438301086426},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.47109255194664},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4698561429977417},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4637869596481323},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4468574821949005},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3989924490451813},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3642672598361969},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15463602542877197}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.730177104473114},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7126255035400391},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6931988000869751},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5901749730110168},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5561208724975586},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.513461172580719},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.48058438301086426},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.47109255194664},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4698561429977417},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4637869596481323},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4468574821949005},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3989924490451813},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3642672598361969},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15463602542877197},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1049/cvi2.12297","is_oa":true,"landing_page_url":"https://doi.org/10.1049/cvi2.12297","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cvi2.12297","source":{"id":"https://openalex.org/S166929102","display_name":"IET Computer Vision","issn_l":"1751-9632","issn":["1751-9632","1751-9640"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Computer Vision","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e1f89c9c9f884afb91311d910460feb0","is_oa":true,"landing_page_url":"https://doaj.org/article/e1f89c9c9f884afb91311d910460feb0","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IET Computer Vision, Vol 18, Iss 8, Pp 1138-1148 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1049/cvi2.12297","is_oa":true,"landing_page_url":"https://doi.org/10.1049/cvi2.12297","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cvi2.12297","source":{"id":"https://openalex.org/S166929102","display_name":"IET Computer Vision","issn_l":"1751-9632","issn":["1751-9632","1751-9640"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Computer Vision","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.75}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400056070.pdf"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1959608418","https://openalex.org/W2019014808","https://openalex.org/W2064029323","https://openalex.org/W2122646361","https://openalex.org/W2132870739","https://openalex.org/W2138621090","https://openalex.org/W2145094598","https://openalex.org/W2599354622","https://openalex.org/W2740924709","https://openalex.org/W2750384547","https://openalex.org/W2900023892","https://openalex.org/W2902758299","https://openalex.org/W2953791858","https://openalex.org/W2963045681","https://openalex.org/W2963049059","https://openalex.org/W2963373786","https://openalex.org/W2986944522","https://openalex.org/W2987228832","https://openalex.org/W2997574889","https://openalex.org/W3006520502","https://openalex.org/W3033696290","https://openalex.org/W3034292309","https://openalex.org/W3040266635","https://openalex.org/W3040536599","https://openalex.org/W3097652626","https://openalex.org/W3106848223","https://openalex.org/W3117272077","https://openalex.org/W3135550350","https://openalex.org/W3157975240","https://openalex.org/W3159911466","https://openalex.org/W3167437959","https://openalex.org/W3200806003","https://openalex.org/W3212220920","https://openalex.org/W4206331418","https://openalex.org/W4231258501","https://openalex.org/W4238940159","https://openalex.org/W4249009392","https://openalex.org/W4255556797","https://openalex.org/W4285531802","https://openalex.org/W4287122441","https://openalex.org/W4289303889","https://openalex.org/W4293568373","https://openalex.org/W4301508264","https://openalex.org/W4312251982","https://openalex.org/W4312570668","https://openalex.org/W4312776882","https://openalex.org/W4319299835","https://openalex.org/W4320013936","https://openalex.org/W4386065890","https://openalex.org/W4394596529","https://openalex.org/W6631190155","https://openalex.org/W6640963894","https://openalex.org/W6761412048","https://openalex.org/W6780248173"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W3194885736","https://openalex.org/W3046391934","https://openalex.org/W4363671829","https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4281663961","https://openalex.org/W3208888551","https://openalex.org/W4313561566","https://openalex.org/W3208386644"],"abstract_inverted_index":{"Abstract":[0],"Anomaly":[1],"Detection,":[2],"also":[3],"known":[4],"as":[5,13],"outlier":[6],"detection,":[7,17],"is":[8,27],"critical":[9],"in":[10,219],"domains":[11],"such":[12],"network":[14],"security,":[15],"intrusion":[16],"and":[18,56,104,192,222,238,255],"fraud":[19],"detection.":[20,136],"One":[21],"popular":[22],"approach":[23],"to":[24,33,119,134,144,163,196,225],"anomaly":[25,135,216],"detection":[26,217,260],"using":[28],"autoencoders,":[29],"which":[30,60],"are":[31],"trained":[32],"reconstruct":[34],"input":[35],"by":[36,75],"minimising":[37],"reconstruction":[38,54,58,106,116,161,166,194],"error":[39],"with":[40],"the":[41,50,62,68,79,87,111,115,123,138,146,152,160,170,180,183,189,193,206,210,213,220,241,244,252],"neural":[42],"network.":[43],"However,":[44],"these":[45],"methods":[46],"usually":[47],"suffer":[48],"from":[49],"trade\u2010off":[51,70],"between":[52],"normal":[53,149],"fidelity":[55],"abnormal":[57,227],"distinguishability,":[59],"damages":[61],"performance.":[63,178,261],"The":[64,108],"authors":[65,88,139,184,214],"find":[66],"that":[67,96,249],"above":[69],"can":[71,258],"be":[72],"better":[73],"mitigated":[74],"imposing":[76],"constraints":[77,121,250],"on":[78,122,176,232,251],"latent":[80,124,223,253],"space":[81,125,254],"of":[82,98,126,148,172,188,243],"images.":[83],"To":[84],"this":[85],"end,":[86],"propose":[89],"a":[90,99,105],"new":[91],"Dual":[92],"Adversarial":[93],"Network":[94],"(DualAD)":[95],"consists":[97],"Feature":[100],"Constraint":[101],"(FC)":[102],"module":[103,113,191,195],"module.":[107],"method":[109],"incorporates":[110],"FC":[112,190],"during":[114,159],"training":[117,187],"process":[118,162],"impose":[120],"images,":[127],"thereby":[128,168],"yielding":[129],"feature":[130,199,207],"representations":[131],"more":[132,203,229],"conducive":[133],"Additionally,":[137],"employ":[140],"dual":[141],"adversarial":[142,155,186,256],"learning":[143,156,257],"model":[145,177],"distribution":[147],"data.":[150],"On":[151,179],"one":[153],"hand,":[154,182],"was":[157],"implemented":[158],"obtain":[164],"higher\u2010quality":[165],"samples,":[167],"preventing":[169],"effects":[171],"blurred":[173],"image":[174],"reconstructions":[175],"other":[181],"utilise":[185],"achieve":[197],"superior":[198],"representation,":[200],"making":[201],"anomalies":[202],"distinguishable":[204],"at":[205],"level.":[208],"During":[209],"inference":[211],"phase,":[212],"perform":[215],"simultaneously":[218],"pixel":[221],"spaces":[224],"identify":[226],"patterns":[228],"comprehensively.":[230],"Experiments":[231],"three":[233],"data":[234],"sets":[235],"CIFAR10,":[236],"MNIST,":[237],"FashionMNIST":[239],"demonstrate":[240],"validity":[242],"authors\u2019":[245],"work.":[246],"Results":[247],"show":[248],"improve":[259]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
