Permute-MAML: exploring industrial surface defect detection algorithms for few-shot learning

Permute-MAML: exploring industrial surface defect detection algorithms for few-shot learning

Abstract Computer vision has developed rapidly in recent years, invigorating the area of industrial surface defect detection while also providing it with modern perception capabilities. Few-shot learning has emerged as a result of sample size limitations, with MAML framework being the most widely us...

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Detaylı Bibliyografya
Asıl Yazarlar: ShanChen Pang, WenShang Zhao, ShuDong Wang, Lin Zhang, Shuang Wang
Materyal Türü: Makale
Dil:English
Baskı/Yayın Bilgisi: Springer 2023-09-01
Seri Bilgileri:Complex & Intelligent Systems
Konular:
Computer vision
Few-shot learning
Industrial surface defect detection
Permute-MAML
Online Erişim:https://doi.org/10.1007/s40747-023-01219-9

Internet

https://doi.org/10.1007/s40747-023-01219-9

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