most citedSqueezed Convolutional Variational AutoEncoder for Unsupervised Anomaly Detection in Edge Device Industrial Internet of Things

6 citations · 6 across the 1 of their papers we have counts for

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1 paper

cs.LG2017★ 6 cited

Squeezed Convolutional Variational AutoEncoder for Unsupervised Anomaly Detection in Edge Device Industrial Internet of Things

Dohyung Kim, Hyochang Yang, Minki Chung +1

In this paper, we propose Squeezed Convolutional Variational AutoEncoder (SCVAE) for anomaly detection in time series data for Edge Computing in Industrial Internet of Things (IIoT…