HIGHLIGHTS
- who: Walaa Gouda and colleagues from the Department of Computer Engineering and Network, College of Computer and Information Sciences, Jouf University, Sakaka, Al Jouf, Saudi Arabia have published the research: Unsupervised Outlier Detection in IOT Using Deep VAE, in the Journal: Sensors 2022, 6617 of /2022/
- what: The authors propose an unsupervised technique based on a deep Variational Auto-Encoder (VAE) to detect outliers in IoT data by leveraging the characteristic of the reconstruction ability and the low-dimensional representation of the input data`s latent variables of the VAE. The unsupervised abnormality detection challenges . . .
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