Abstract

This paper summarizes the theory behind state-of-the-art convolutional neural networks and investigates how they can applied to some of the challenges in Industry 4.0. Following an overview of key results in the literature, several major application areas are highlighted, with a focus on areas such as defect detection in production and anomaly detection for maintenance. It is concluded that convolutional neural networks are essential tools for solving many challenges in Industry 4.0.

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