| Autor: |
Mou, Shancong, Cao, Meng, Hong, Zhendong, Huang, Ping, Shan, Jiulong, Shi, Jianjun |
| Rok vydání: |
2022 |
| Předmět: |
|
| Druh dokumentu: |
Working Paper |
| Popis: |
Display front-of-screen (FOS) quality inspection is essential for the mass production of displays in the manufacturing process. However, the severe imbalanced data, especially the limited number of defect samples, has been a long-standing problem that hinders the successful application of deep learning algorithms. Synthetic defect data generation can help address this issue. This paper reviews the state-of-the-art synthetic data generation methods and the evaluation metrics that can potentially be applied to display FOS quality inspection tasks. |
| Databáze: |
arXiv |
| Externí odkaz: |
|
