Deep Learning: Image anomaly detection for production line ~

版本 1.0.1 (12.8 MB) 作者: Takuji Fukumoto
Use pre-trained AlexNet and 1-class SVM for anomaly detection
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1.3K 次下载
更新时间 2020/12/25
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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

引用格式

Takuji Fukumoto (2024). 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. 检索来源 .

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版本 已发布 发行说明
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

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要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。