Application of the Attention-Guided Neural Network for the Defects Detection
Application of the Attention-Guided Neural Network for the Defects Detection
Thursday, October 31, 2024
Indigo Ballroom (Hilton San Diego Bayfront)
Summary:
The Attention-Guided Neural Network is designed to analyze periodic SEM images of SRAM. Autoencoder latent features layer is used to reconstruct the crops of the original image. By thresholding the ability of the autoencoder to reconstruct the original image, the defects and artifacts of the original image are automatically located. This approach could be used to detect visual anomalies.
The Attention-Guided Neural Network is designed to analyze periodic SEM images of SRAM. Autoencoder latent features layer is used to reconstruct the crops of the original image. By thresholding the ability of the autoencoder to reconstruct the original image, the defects and artifacts of the original image are automatically located. This approach could be used to detect visual anomalies.