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coreloss's Introduction

Coreloss

Core Loss：污染数据下基于Autoencoder的无监督异常检测损失。

Core Loss: Unsupervised Anomaly Detection under Data Pollution

A plug-and-play replacement for MSE loss!

Use case is shown in Script_coreloss.py. Can runing on the environment with pytorch 1.9

If you're intrested in this work, please cite it!

@article{shang2023core,
  title={Core loss: Mining core samples efficiently for robust machine anomaly detection against data pollution},
  author={Shang, Zuogang and Zhao, Zhibin and Yan, Ruqiang and Chen, Xuefeng},
  journal={Mechanical Systems and Signal Processing},
  volume={189},
  pages={110046},
  year={2023},
  publisher={Elsevier}
}

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coreloss's Issues

update code

A great work. I read your paper and come here. Would you please update the code as soon as possible?

cheers!

求代码

我是一位做异常检测的初学者，请问您方便提供一份如您的论文4.4节(Experimental verification with IMS bearing dataset)中所述的轴承异常检测的代码吗？包含轴承数据的读取、模型训练、阈值计算和测试等一整套完整的流程。

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