# 10 - Anomaly Detection with Computer Vision in Manufacturing

Complete guide to Anomaly Detection with Computer Vision in Manufacturing: architecture, practical implementation and best practices for developers and technical teams.

## What you'll learn

- Anomaly detection approaches: supervised, semi-supervised, unsupervised
- MVTec Anomaly Detection Dataset: the standard industrial benchmark
- PatchCore: state-of-the-art algorithm for unsupervised anomaly detection
- Handling class imbalance in real defect datasets
- Domain-specific data augmentation for industrial images

*This article is part of the **Computer Vision** series on federicocalo.dev.*

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## Read the full article

The complete article (18 min read) with code examples, diagrams, and practical exercises is available here:

**➡️ [10 - Anomaly Detection with Computer Vision in Manufacturing](https://federicocalo.dev/en/blog/anomaly-detection-computer-vision-manufacturing)**

`https://federicocalo.dev/en/blog/anomaly-detection-computer-vision-manufacturing`

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*By [Federico Calò](https://federicocalo.dev) — Software Developer & Technical Writer*