{"id":"https://openalex.org/W4416250734","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227359","title":"Few-shot Anomaly Detection Based on Diffusion Generation Model and Multi-scale Feature Manipulation","display_name":"Few-shot Anomaly Detection Based on Diffusion Generation Model and Multi-scale Feature Manipulation","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250734","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227359"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227359","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5078071027","display_name":"Shu Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]},{"id":"https://openalex.org/I4210115456","display_name":"Chuzhou University","ror":"https://ror.org/037663q52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115456"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shu Zhao","raw_affiliation_strings":["Anhui University,School of Computer Science and Technology,Hefei,China","Chuzhou University,School of Artificial Intelligence,Chuzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University,School of Computer Science and Technology,Hefei,China","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"Chuzhou University,School of Artificial Intelligence,Chuzhou,China","institution_ids":["https://openalex.org/I4210115456"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346416","display_name":"Ao Liu","orcid":"https://orcid.org/0000-0002-4529-0748"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ao Liu","raw_affiliation_strings":["Anhui University,School of Computer Science and Technology,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University,School of Computer Science and Technology,Hefei,China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082763700","display_name":"Dingjun Qu","orcid":"https://orcid.org/0000-0001-8175-4979"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I2802624667","display_name":"Hefei Institutes of Physical Science","ror":"https://ror.org/046n57345","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I2802624667"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingjun Qu","raw_affiliation_strings":["Chinese Academy of Sciences,Hefei Institutes of Physical Science,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Hefei Institutes of Physical Science,Hefei,China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I2802624667"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077965872","display_name":"Shenghui Zhao","orcid":"https://orcid.org/0000-0002-0844-2319"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]},{"id":"https://openalex.org/I4210115456","display_name":"Chuzhou University","ror":"https://ror.org/037663q52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115456"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenghui Zhao","raw_affiliation_strings":["Anhui University,School of Computer Science and Technology,Hefei,China","Chuzhou University,School of Artificial Intelligence,Chuzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University,School of Computer Science and Technology,Hefei,China","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"Chuzhou University,School of Artificial Intelligence,Chuzhou,China","institution_ids":["https://openalex.org/I4210115456"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"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":0.9763000011444092,"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":0.9763000011444092,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0017999999690800905,"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/T12127","display_name":"Software System Performance and Reliability","score":0.0017000000225380063,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7925999760627747},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6789000034332275},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6646000146865845},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6575999855995178},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6090999841690063},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.607200026512146},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5473999977111816}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7925999760627747},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6789000034332275},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6646000146865845},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6575999855995178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6518999934196472},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6503000259399414},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6090999841690063},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.607200026512146},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5473999977111816},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49070000648498535},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3296000063419342},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2928999960422516},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2685000002384186},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2669999897480011}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227359","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2948982773","https://openalex.org/W2963733773","https://openalex.org/W3107803166","https://openalex.org/W3120387510","https://openalex.org/W3147184966","https://openalex.org/W3169651898","https://openalex.org/W4214694907","https://openalex.org/W4312298392","https://openalex.org/W4312605624","https://openalex.org/W4317528903","https://openalex.org/W4324142429","https://openalex.org/W4382240612","https://openalex.org/W4386065385","https://openalex.org/W4386075837","https://openalex.org/W4392196931","https://openalex.org/W4392930642","https://openalex.org/W4393147399","https://openalex.org/W4394597750","https://openalex.org/W4402733578"],"related_works":[],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,15,61],"(AD)":[2],"is":[3],"crucial":[4],"in":[5,9,29],"industrial":[6],"production,":[7],"particularly":[8],"the":[10,23,50,60,102,116,137,149,176],"context":[11],"of":[12,25,42,64,168,173],"few-shot":[13],"anomaly":[14,81,154,158],"(FSAD),":[16],"which":[17,78],"has":[18],"gained":[19],"attention":[20],"due":[21],"to":[22,45,97,118,156],"challenges":[24],"obtaining":[26],"labeled":[27],"samples":[28,44,133],"real-world":[30],"scenarios.":[31],"Existing":[32],"FSAD":[33,187],"methods":[34],"generate":[35],"synthetic":[36],"anomalies":[37,52,100],"from":[38,56,101],"a":[39,72,92],"limited":[40,103],"number":[41],"normal":[43,104],"augment":[46],"training":[47],"data.":[48],"However,":[49],"generated":[51,135],"often":[53],"diverge":[54],"significantly":[55,183],"actual":[57],"anomalies,":[58],"complicating":[59],"and":[62,106,136,146,170,179],"localization":[63],"defects.":[65],"To":[66],"address":[67],"this":[68],"challenge,":[69],"we":[70,107,152],"introduce":[71],"novel":[73],"discriminative":[74],"network":[75],"named":[76],"DiscNetAD,":[77],"integrates":[79],"realistic":[80,99,131],"generation":[82],"with":[83],"image":[84,110],"pyramid":[85,111],"decomposition":[86],"for":[87,112],"FSAD.":[88],"Our":[89],"approach":[90],"employs":[91],"diffusion":[93],"model-based":[94],"generative":[95],"strategy":[96],"create":[98],"samples,":[105],"utilize":[108],"an":[109],"multi-scale":[113],"decomposition,":[114],"allowing":[115],"model":[117,138],"capture":[119],"fine-grained":[120],"features":[121],"across":[122],"various":[123,141],"resolutions.":[124],"By":[125],"performing":[126],"these":[127],"two":[128],"operations,":[129],"more":[130],"anomalous":[132],"are":[134],"can":[139],"identify":[140],"anomalies.":[142],"After":[143],"feature":[144],"extraction":[145],"aggregation":[147],"on":[148,175],"decomposed":[150],"images,":[151],"apply":[153],"discriminators":[155],"estimate":[157],"scores.":[159],"Comprehensive":[160],"evaluations":[161],"demonstrate":[162],"that":[163],"DiscNetAD":[164],"achieves":[165],"image-level/pixel-level":[166,171],"AUROC":[167,172],"97.5%/98.1%":[169],"89.5%/97.9%":[174],"MVTec":[177],"AD":[178],"VisA":[180],"datasets,":[181],"respectively,":[182],"outperforming":[184],"current":[185],"state-of-the-art":[186],"methods.":[188]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-11-14T00:00:00"}