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