ESAD: End-to-end Deep Semi-supervised Anomaly Detection

Chaoqin Huang, Fei Ye, Peisen Zhao +3

This paper explores semi-supervised anomaly detection, a more practical setting for anomaly detection where a small additional set of labeled samples are provided. We propose a new…