Deep Learning: Image anomaly detection for production line ~

versión 1.0.1 (12.3 MB) por Takuji Fukumoto
Use pre-trained AlexNet and 1-class SVM for anomaly detection

1,1K descargas

Actualizada 25 Dec 2020

De GitHub

Ver licencia en GitHub

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 (2022). 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 .

Compatibilidad con la versión de MATLAB
Se creó con R2017a
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Para consultar o informar de algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
Para consultar o informar de algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.