{"id":"https://openalex.org/W7125899407","doi":"https://doi.org/10.1109/tetci.2026.3654456","title":"Not Only Detection But Also Explain: An Interpretable Multimodal System for Anomaly Detection","display_name":"Not Only Detection But Also Explain: An Interpretable Multimodal System for Anomaly Detection","publication_year":2026,"publication_date":"2026-01-28","ids":{"openalex":"https://openalex.org/W7125899407","doi":"https://doi.org/10.1109/tetci.2026.3654456"},"language":null,"primary_location":{"id":"doi:10.1109/tetci.2026.3654456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2026.3654456","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-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/A5124124853","display_name":"Chih-Yung Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I107470533","display_name":"Tamkang University","ror":"https://ror.org/04tft4718","country_code":"TW","type":"education","lineage":["https://openalex.org/I107470533"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Chih-Yung Chang","raw_affiliation_strings":["Department of Computer Science and Information Engineering, Tamkang University, Taipei, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-0672-5593","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, Tamkang University, Taipei, Taiwan","institution_ids":["https://openalex.org/I107470533"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047519765","display_name":"Wendong Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I107470533","display_name":"Tamkang University","ror":"https://ror.org/04tft4718","country_code":"TW","type":"education","lineage":["https://openalex.org/I107470533"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wen-Dong Jiang","raw_affiliation_strings":["Department of Computer Science and Information Engineering, Tamkang University, Taipei, Taiwan"],"raw_orcid":"https://orcid.org/0009-0000-7969-6386","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, Tamkang University, Taipei, Taiwan","institution_ids":["https://openalex.org/I107470533"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120971606","display_name":"I-Hsiung Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I64045040","display_name":"Fooyin University","ror":"https://ror.org/03pfmgq50","country_code":"TW","type":"education","lineage":["https://openalex.org/I64045040"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"I-Hsiung Chang","raw_affiliation_strings":["Department of Child Care and Education, Fooying University, Kaohsiung, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Child Care and Education, Fooying University, Kaohsiung, Taiwan","institution_ids":["https://openalex.org/I64045040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011943818","display_name":"Diptendu Sinha Roy","orcid":"https://orcid.org/0000-0001-9731-2534"},"institutions":[{"id":"https://openalex.org/I9523339","display_name":"National Institute of Technology Meghalaya","ror":"https://ror.org/020vd6n84","country_code":"IN","type":"education","lineage":["https://openalex.org/I9523339"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Diptendu Sinha Roy","raw_affiliation_strings":["Department of Computer Science and Engineering, National Institute of Technology, Shillong, India"],"raw_orcid":"https://orcid.org/0000-0001-9731-2534","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, National Institute of Technology, Shillong, India","institution_ids":["https://openalex.org/I9523339"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5124124853"],"corresponding_institution_ids":["https://openalex.org/I107470533"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16829937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"2","first_page":"1863","last_page":"1877"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9605000019073486,"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":0.9605000019073486,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.006099999882280827,"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":0.004699999932199717,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.8770999908447266},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7508000135421753},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5529000163078308},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.513700008392334},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5008999705314636},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4611000120639801},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4156000018119812},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.3276999890804291}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8770999908447266},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7508000135421753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.704200029373169},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6498000025749207},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5529000163078308},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.513700008392334},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5008999705314636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4702000021934509},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4611000120639801},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4156000018119812},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35850000381469727},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.32690000534057617},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.32359999418258667},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C2778971668","wikidata":"https://www.wikidata.org/wiki/Q5510284","display_name":"Fusion rules","level":4,"score":0.28119999170303345},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C84839998","wikidata":"https://www.wikidata.org/wiki/Q5249245","display_name":"Decision rule","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2540000081062317},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2026.3654456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2026.3654456","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7266908884048462,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F2461203286","display_name":"National Science and Technology Council","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Anomaly":[0],"detection":[1],"is":[2],"often":[3],"formulated":[4],"as":[5],"a":[6,118,129],"Multiple":[7],"Instance":[8],"Learning":[9],"(MIL)":[10],"problem,":[11],"where":[12],"an":[13,64],"anomaly":[14,20],"detector":[15],"learns":[16],"to":[17,52,103,124,132],"generate":[18],"frame-level":[19,123],"scores":[21],"under":[22],"multi-modal":[23,88],"supervision.":[24],"However,":[25],"most":[26],"previous":[27],"studies":[28],"have":[29],"two":[30],"drawbacks:":[31],"1)":[32],"the":[33,39,44,86,105,114,133,140,155,162],"feature":[34,111],"fusion":[35,89,98],"between":[36],"attributes":[37],"overlooks":[38],"model\u2019s":[40,156],"interpretability;":[41],"and":[42,91,176],"2)":[43],"training":[45,55,94,150],"strategy":[46],"based":[47],"on":[48],"pre-trained":[49],"models":[50],"leads":[51],"excessively":[53],"long":[54],"times.":[56],"To":[57],"address":[58],"these":[59],"issues,":[60],"this":[61],"paper":[62],"proposes":[63],"<underline":[65,68,71,74,77],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[66,69,72,75,78],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">I</u>nterpretable":[67],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">M</u>ulti-modal":[70],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">A</u>nomaly":[73],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">D</u>etection":[76],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">S</u>ystem":[79],"called":[80],"IMADS.":[81],"The":[82],"proposed":[83,115,163],"IMADS":[84,116,164],"abandons":[85],"traditional":[87,110],"approach":[90,146],"adopts":[92],"single-modal":[93],"with":[95],"late-stage":[96],"decision":[97],"optimized":[99],"by":[100,109,136],"Bayesian":[101],"techniques":[102],"resolve":[104],"interpretability":[106],"problem":[107],"caused":[108],"fusion.":[112],"Moreover,":[113],"introduces":[117],"transfer":[119],"learning":[120],"method":[121],"from":[122],"video-level,":[125],"which":[126],"essentially":[127],"adds":[128],"temporal":[130],"dimension":[131,142],"2D-to-3D":[134],"conversion":[135],"randomizing":[137],"parameters":[138],"along":[139],"time":[141],"during":[143],"training.":[144],"This":[145],"not":[147],"only":[148],"improves":[149],"efficiency":[151],"but":[152],"also":[153],"ensures":[154],"interpretability.":[157],"Experimental":[158],"results":[159],"demonstrate":[160],"that":[161],"significantly":[165],"outperforms":[166],"existing":[167],"methods":[168],"in":[169],"terms":[170],"of":[171],"performance,":[172],"proving":[173],"its":[174],"innovativeness":[175],"effectiveness.":[177]},"counts_by_year":[],"updated_date":"2026-04-30T09:15:22.047038","created_date":"2026-01-29T00:00:00"}
