Deep Learning: Image anomaly detection for production line ~

Use pre-trained AlexNet and 1-class SVM for anomaly detection

https://github.com/mathworks/Deep-Learning-Image-anomaly-detection-for-production-line

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When we apply deeplearning to anomaly detection for image on production line, there are few abnomal units to train your classifier.
Through this demo, you can learn how to try anomaly detection without training data of abnomal unit and labeling.
-kernel methods with 1class SVM and pre-trained AlexNet
-focus on production line and manufacturing.
-unsupervised classification (without labeling)
-feature visualization with t-SNE
This demo include hundreds training and test images. So you can try this now.

You can download the AlexNet support package here:
https://www.mathworks.com/matlabcentral/fileexchange/59133-neural-network-toolbox-tm--model-for-alexnet-network

Citar como

Takuji Fukumoto (2026). Deep Learning: Image anomaly detection for production line ~ (https://github.com/mathworks/Deep-Learning-Image-anomaly-detection-for-production-line/releases/tag/1.0.1), GitHub. Recuperado .

Categorías

Más información sobre Deep Learning Toolbox en Help Center y MATLAB Answers.

Información general

Compatibilidad con la versión de MATLAB

  • Compatible con cualquier versión

Compatibilidad con las plataformas

  • Windows
  • macOS
  • Linux
Versión Publicado Notas de la versión Action
1.0.1

See release notes for this release on GitHub: https://github.com/mathworks/Deep-Learning-Image-anomaly-detection-for-production-line/releases/tag/1.0.1

1.0.0.0

Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.