Visual inspection is the image-based inspection of parts where a camera scans the part under test for failures and quality defects. By using
deep learning and
computer vision techniques, visual inspection can be automated for detecting manufacturing flaws in many industries such as biotech, automotive, and semiconductors. For example, with visual inspection, flaws can be detected in semiconductor wafers and pills.
Watch the following video that walks you through the steps of a visual inspection workflow using a ResNet
convolutional neural network. MATLAB provides access to many
pretrained deep learning models that you can use for visual inspection. For more visual inspection examples, see
Automated Visual Inspection.
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