Synthetic Defect Generation for Display Front-of-Screen Quality Inspection: A Survey
AuthorsShancong Mou, Meng Cao, Zhendong Hong, Ping Huang, Jiulong Shan, Jianjun Shi
AuthorsShancong Mou, Meng Cao, Zhendong Hong, Ping Huang, Jiulong Shan, Jianjun Shi
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 defective 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.
March 13, 2023research area Computer Vision, research area Methods and Algorithmsconference IISE Transactions
May 23, 2022research area Speech and Natural Language Processingconference ICASSP