{"id":"https://openalex.org/W7135155135","doi":"https://doi.org/10.1109/tip.2026.3671617","title":"Few-Shot Strip Steel Surface Defect Segmentation via Pre-Trained Variational Auto-Encoder-Based Latent Gaussian Process Regression","display_name":"Few-Shot Strip Steel Surface Defect Segmentation via Pre-Trained Variational Auto-Encoder-Based Latent Gaussian Process Regression","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7135155135","doi":"https://doi.org/10.1109/tip.2026.3671617","pmid":"https://pubmed.ncbi.nlm.nih.gov/41818006"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3671617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3671617","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/A5128880750","display_name":"Xiaofei Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofei Zhou","raw_affiliation_strings":["School of Automation, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7977-9728","affiliations":[{"raw_affiliation_string":"School of Automation, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115694805","display_name":"Xuan Wang","orcid":"https://orcid.org/0000-0002-4160-0761"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Wang","raw_affiliation_strings":["School of Automation, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061140967","display_name":"Gongyang Li","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gongyang Li","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-7324-1196","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128827890","display_name":"Deyang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I46482218","display_name":"Anqing Normal University","ror":"https://ror.org/0127ytz78","country_code":"CN","type":"education","lineage":["https://openalex.org/I46482218"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deyang Liu","raw_affiliation_strings":["School of Computer and Information, Anqing Normal University, Anqing, China"],"raw_orcid":"https://orcid.org/0000-0001-7991-8735","affiliations":[{"raw_affiliation_string":"School of Computer and Information, Anqing Normal University, Anqing, China","institution_ids":["https://openalex.org/I46482218"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043694321","display_name":"Qingshan She","orcid":"https://orcid.org/0000-0001-5206-9833"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingshan She","raw_affiliation_strings":["School of Automation, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5206-9833","affiliations":[{"raw_affiliation_string":"School of Automation, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074117281","display_name":"Xiaobin Xu","orcid":"https://orcid.org/0000-0003-1822-6190"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobin Xu","raw_affiliation_strings":["China-Austria Belt and Road Joint Laboratory on Artificial Intelligence and Advanced Manufacturing, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1822-6190","affiliations":[{"raw_affiliation_string":"China-Austria Belt and Road Joint Laboratory on Artificial Intelligence and Advanced Manufacturing, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128818814","display_name":"Runmin Cong","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runmin Cong","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0003-0972-4008","affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32854836,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"2771","last_page":"2786"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.17110000550746918,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.17110000550746918,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.15559999644756317,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11948","display_name":"Machine Learning in Materials Science","score":0.06319999694824219,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5738000273704529},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5672000050544739},{"id":"https://openalex.org/keywords/strip-steel","display_name":"Strip steel","score":0.5340999960899353},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5230000019073486},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.49070000648498535},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.44850000739097595},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43389999866485596},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.39649999141693115},{"id":"https://openalex.org/keywords/strips","display_name":"STRIPS","score":0.3693000078201294}],"concepts":[{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5738000273704529},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5672000050544739},{"id":"https://openalex.org/C2780242121","wikidata":"https://www.wikidata.org/wiki/Q7624097","display_name":"Strip steel","level":2,"score":0.5340999960899353},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5230000019073486},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.49070000648498535},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4575999975204468},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.44850000739097595},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43619999289512634},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43389999866485596},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40459999442100525},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.39649999141693115},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37369999289512634},{"id":"https://openalex.org/C200925200","wikidata":"https://www.wikidata.org/wiki/Q7624170","display_name":"STRIPS","level":2,"score":0.3693000078201294},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.359499990940094},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3422999978065491},{"id":"https://openalex.org/C20885615","wikidata":"https://www.wikidata.org/wiki/Q825595","display_name":"Surface reconstruction","level":3,"score":0.33730000257492065},{"id":"https://openalex.org/C185568154","wikidata":"https://www.wikidata.org/wiki/Q530242","display_name":"Mathematical morphology","level":4,"score":0.33649998903274536},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C2984999661","wikidata":"https://www.wikidata.org/wiki/Q603159","display_name":"Surface fitting","level":3,"score":0.30079999566078186},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.29409998655319214},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.28290000557899475},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2761000096797943},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2547999918460846},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.251800000667572},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.25040000677108765}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3671617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3671617","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:41818006","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41818006","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/G1914386590","display_name":null,"funder_award_id":"62471278","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5426400494","display_name":null,"funder_award_id":"62401350","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5574733590","display_name":null,"funder_award_id":"62371172","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7596411858","display_name":null,"funder_award_id":"62271180","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"few-shot":[1,16,55],"strip":[2,56],"steel":[3,57],"surface":[4,58],"defect":[5,59,98],"segmentation":[6,17],"has":[7],"received":[8],"more":[9,11],"and":[10,31,73,122,133,151,162,183],"concerns.":[12],"However,":[13],"the":[14,21,28,66,80,94,108,114,163,173,181],"existing":[15],"methods":[18],"usually":[19],"adopt":[20],"frozen":[22,67],"encoder,":[23,116],"which":[24,75],"is":[25,131],"pre-trained":[26,44,77],"on":[27,158],"classification":[29],"task":[30,83],"can":[32,87,125],"only":[33],"provide":[34,88],"class-related":[35],"knowledge.":[36,91],"Therefore,":[37],"we":[38,140],"propose":[39],"a":[40,103,177],"novel":[41],"method,":[42],"namely":[43],"variational":[45],"auto-encoder":[46],"based":[47,71],"latent":[48,109],"gaussian":[49,104],"process":[50,105],"regression":[51,106],"(LGPR),":[52],"to":[53,144],"conduct":[54],"segmentation.":[60],"Firstly,":[61],"different":[62],"from":[63],"previous":[64],"methods,":[65],"Variational":[68],"Auto-Encoder":[69],"(VAE)":[70],"encoder":[72],"decoder,":[74],"are":[76,156,185],"by":[78,101,113],"using":[79],"pixel-level":[81,117],"self-supervised":[82],"(i.e.,":[84],"image":[85],"reconstruction),":[86],"rich":[89],"image-related":[90],"This":[92,129],"ensures":[93],"effective":[95],"characterization":[96],"of":[97,149],"regions.":[99],"Secondly,":[100],"deploying":[102],"in":[107],"feature":[110],"space":[111],"generated":[112],"VAE-based":[115],"correlation":[118],"between":[119],"support":[120,150],"features":[121,124],"query":[123,152],"be":[126],"efficiently":[127],"built.":[128],"operation":[130],"non-parametric":[132],"doesn't":[134],"bring":[135],"any":[136],"training":[137],"overhead.":[138],"Besides,":[139],"deploy":[141],"transformer-based":[142],"projectors":[143],"dig":[145],"long-range":[146],"contextual":[147],"cues":[148],"features.":[153],"Extensive":[154],"experiments":[155],"performed":[157],"two":[159],"public":[160],"datasets,":[161],"experimental":[164],"results":[165,184],"clearly":[166],"show":[167],"that":[168],"our":[169],"model":[170],"consistently":[171],"outperforms":[172],"state-of-the-art":[174],"models":[175],"with":[176],"large":[178],"margin.":[179],"Both":[180],"codes":[182],"publicly":[186],"available":[187],"at":[188],"https://github.com/Hlao-hub/LGPR.":[189]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-13T00:00:00"}
