项目作者: YeongHyeon

项目描述 :
高级语言: Python
项目地址: git://github.com/YeongHyeon/CVAE-AnomalyDetection-TF2.git
创建时间: 2019-12-02T10:30:00Z
项目社区:https://github.com/YeongHyeon/CVAE-AnomalyDetection-TF2

开源协议:MIT License

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[TensorFlow 2] Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)

Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE) [Related repository] [PyTorch Version].

Architecture



Simplified VAE architecture.


Problem Definition



‘Class-1’ is defined as normal and the others are defined as abnormal.


Results

Training



Restoration result by CVAE.




Latent vector space of training set, and reconstruction result of latent space walking.


Test

z_dim = 2



Left figure shows latent vector space of test set. Right figure shows box plot with restoration loss of test procedure.


z_dim = 128



Latent vector space of test set, box plot with restoration loss, and histogram of restoration loss.


Environment

  • Python 3.7.4
  • Tensorflow 2.1.0
  • Numpy 1.17.1
  • Matplotlib 3.1.1
  • Scikit Learn (sklearn) 0.21.3

Reference

[1] Kingma, D. P., & Welling, M. (2013). Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114.
[2] Kullback Leibler divergence. Wikipedia