{"id":"https://openalex.org/W7127588467","doi":"https://doi.org/10.1109/tip.2026.3659292","title":"Improving Unsupervised Ultrasonic Image Anomaly Detection via Frequency-Spatial Feature Filtering and Gaussian Mixture Modeling","display_name":"Improving Unsupervised Ultrasonic Image Anomaly Detection via Frequency-Spatial Feature Filtering and Gaussian Mixture Modeling","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7127588467","doi":"https://doi.org/10.1109/tip.2026.3659292","pmid":"https://pubmed.ncbi.nlm.nih.gov/41637709"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3659292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3659292","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5124999358","display_name":"Wenjing Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenjing Zhang","raw_affiliation_strings":["School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124995730","display_name":"Ke Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Lu","raw_affiliation_strings":["School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jinbao Wang","orcid":"https://orcid.org/0000-0001-5916-8965"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinbao Wang","raw_affiliation_strings":["School of Artificial Intelligence and the National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and the National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113392696","display_name":"H. Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Liang","raw_affiliation_strings":["School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082131990","display_name":"Can Gao","orcid":"https://orcid.org/0009-0005-6279-8286"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Can Gao","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100763213","display_name":"Jian Xue","orcid":"https://orcid.org/0000-0002-9460-802X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Xue","raw_affiliation_strings":["School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5124999358"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27662598,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"1567","last_page":"1581"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.22300000488758087,"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":0.22300000488758087,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.20630000531673431,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.05590000003576279,"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/anomaly-detection","display_name":"Anomaly detection","score":0.6154999732971191},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6140999794006348},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4699000120162964},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.46619999408721924},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.45649999380111694},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4465999901294708},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44519999623298645},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3995000123977661},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3799999952316284},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.322299987077713}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6801000237464905},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6779999732971191},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6154999732971191},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6140999794006348},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4699000120162964},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.46619999408721924},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.45649999380111694},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4465999901294708},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44519999623298645},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3995000123977661},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3540000021457672},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3188000023365021},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C65892221","wikidata":"https://www.wikidata.org/wiki/Q1113935","display_name":"Gaussian filter","level":3,"score":0.29649999737739563},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C81288441","wikidata":"https://www.wikidata.org/wiki/Q20736125","display_name":"Ultrasonic sensor","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2712000012397766},{"id":"https://openalex.org/C104317376","wikidata":"https://www.wikidata.org/wiki/Q1894545","display_name":"Gaussian blur","level":5,"score":0.2639000117778778},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.25859999656677246},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.25760000944137573},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2574000060558319},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3659292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3659292","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:41637709","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41637709","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":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2370570718","display_name":null,"funder_award_id":"2023YFF0716504","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G3137365035","display_name":null,"funder_award_id":"L254018","funder_id":"https://openalex.org/F4320334977","funder_display_name":"Beijing Municipal Natural Science Foundation"},{"id":"https://openalex.org/G6080631168","display_name":null,"funder_award_id":"62206122","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6656811634","display_name":null,"funder_award_id":"62521007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G728368352","display_name":null,"funder_award_id":"62576218","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334977","display_name":"Beijing Municipal Natural Science Foundation","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2793605784","https://openalex.org/W2948982773","https://openalex.org/W2987138151","https://openalex.org/W3169651898","https://openalex.org/W3179138709","https://openalex.org/W3185486439","https://openalex.org/W3191879248","https://openalex.org/W3196165062","https://openalex.org/W3211749075","https://openalex.org/W4221140561","https://openalex.org/W4292851291","https://openalex.org/W4312289809","https://openalex.org/W4312605624","https://openalex.org/W4318831100","https://openalex.org/W4380880327","https://openalex.org/W4385195017","https://openalex.org/W4386065890","https://openalex.org/W4390875033","https://openalex.org/W4392693636","https://openalex.org/W4393147759","https://openalex.org/W4394597908","https://openalex.org/W4394897081","https://openalex.org/W4400070502","https://openalex.org/W4406303235","https://openalex.org/W4406311329","https://openalex.org/W4406456755","https://openalex.org/W4409364302","https://openalex.org/W4409367277","https://openalex.org/W4413147797"],"related_works":[],"abstract_inverted_index":{"Ultrasonic":[0],"image":[1],"anomaly":[2,68,120],"detection":[3],"faces":[4],"significant":[5],"challenges":[6],"due":[7],"to":[8,91,170],"limited":[9],"labeled":[10],"data,":[11],"strong":[12],"structural":[13],"and":[14,17,53,86,110,133,147,172,185],"random":[15],"noise,":[16],"highly":[18],"diverse":[19],"defect":[20],"manifestations.":[21],"To":[22],"overcome":[23],"these":[24],"obstacles,":[25],"we":[26,59,124],"introduce":[27],"UltraChip,":[28],"a":[29,62,78,112,126,139,179],"new":[30],"large-scale":[31],"C-scan":[32],"benchmark":[33],"containing":[34],"about":[35],"8,000":[36],"real-world":[37],"images":[38],"from":[39],"various":[40],"chip":[41],"packaging":[42],"types,":[43],"each":[44],"meticulously":[45],"annotated":[46],"with":[47,138],"pixel-level":[48,119],"masks":[49],"for":[50,67,117],"cracks,":[51],"holes,":[52],"layers.":[54],"Building":[55],"on":[56,162,178],"this":[57],"resource,":[58],"present":[60],"FSGM-Net,":[61],"fully":[63],"unsupervised":[64],"framework":[65,186],"tailored":[66],"detection.":[69],"FSGM-Net":[70,156],"leverages":[71],"an":[72,98],"adaptive":[73],"Frequency-Spatial":[74],"feature":[75,145],"filtering":[76],"mechanism:":[77],"learnable":[79],"FFT-Spatial":[80],"patch":[81,95],"filter":[82,127],"first":[83],"suppresses":[84],"noise":[85],"dynamically":[87],"assigns":[88],"normality":[89],"weights":[90],"Vision":[92],"Transformer":[93],"(ViT)":[94],"features.":[96],"Subsequently,":[97],"Adaptive":[99],"Gaussian":[100,149],"Mixture":[101],"Model":[102],"(Ada-GMM)":[103],"captures":[104],"the":[105,183],"distribution":[106],"of":[107],"normal":[108],"features":[109],"guides":[111],"deep-shallow":[113],"multi-scale":[114],"interaction":[115],"decoder":[116],"accurate,":[118],"inference.":[121],"In":[122],"addition,":[123],"propose":[125],"loss":[128,141],"that":[129,142,155],"enforces":[130],"encoder-filter":[131],"consistency":[132],"entropy-based":[134],"sparse":[135],"gating,":[136],"together":[137],"distributional":[140],"encourages":[143],"both":[144],"reconstruction":[146],"confident":[148],"mixture":[150],"modeling.":[151],"Extensive":[152],"experiments":[153],"demonstrate":[154],"not":[157],"only":[158],"achieves":[159],"state-of-the-art":[160],"results":[161],"UltraChip":[163,196],"but":[164],"also":[165],"exhibits":[166],"superior":[167],"cross-domain":[168],"generalization":[169],"MVTec-AD":[171],"VisA,":[173],"while":[174],"supporting":[175],"real-time":[176],"inference":[177],"single":[180],"GPU.":[181],"Together,":[182],"dataset":[184,197],"advance":[187],"robust,":[188],"annotation-free":[189],"ultrasonic":[190],"NDT":[191],"in":[192],"practical":[193],"applications.":[194],"The":[195],"can":[198],"be":[199],"obtained":[200],"via":[201],"https://iiplab.net/ultrachip/.":[202]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-02-06T00:00:00"}
