Automated Visual Inspection with Deep Learning

Automated inspection and defect detection systems use AI to inspect manufacturing parts for failures and defects. This approach enables industries to automatically detect flaws on manufactured surfaces such as metallic rails, semiconductor wafers, and contact lenses. 
This ebook shows how you can use MATLAB® to develop a deep learning network to detect and classify different types of anomalies.



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You will learn about the three main stages of the defect detection workflow:

1. Preparing data, including denoising, registration, and labeling
2. Building and training a deep learning network
3. Deploying the network to multiple hardware platforms such as CPUs and GPUs

Overview: Visual Inspection

Learn how visual inspection works. Resources cover topics relevant to visual inspection, including image processing, computer vision, and deep learning.

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[eBook] Automated Visual Inspection with Deep Learning

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Develop Machine Learning project with MATLAB, Simulink, and a full set of products for Deep Learning.

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