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System overview of PCB defect detection (To enhance the quality of the data, we applied preprocessing to the PCB dataset. The quantity of the data for training is fulfilled by the data augmentation step, and all the data are inputted into our proposed autoencoder model. After the training, the trained model generates a non-defect image from the defect image, and image subtraction between these two images enables us to find the exact defect shape and location).
