A CNN Approach for Simultaneous Spatiotemporal Fault Interpretation
Convolutional Neural Networks (CNNs) have emerged as one of the most effective tools for image analysis. In this study, we propose a custom-designed CNN architecture to construct a process control scheme based on image data. The product image is partitioned into equal-sized grids, each comprising three channels: i: reference image, ii: shifted image, and iii: their difference, which are individual
