PVIIAD: industrial visual anomaly detection method based on partially visible image inpainting
Crossref DOI link: https://doi.org/10.1007/s11801-026-4081-9
Published Online: 2026-02-10
Published Print: 2026-01
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Wu, Qiliang
Fei, Dongce
Yao, Minghui
Niu, Yan
Wang, Cong
Text and Data Mining valid from 2026-01-01
Version of Record valid from 2026-01-01
Article History
Received: 1 April 2024
Revised: 2 June 2025
First Online: 10 February 2026
Ethics declarations
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: The authors declare no conflict of interest.