In this blog, we discuss about the role of Variation Auto Encoder in detecting anomalies from fetal ECG signals.

Variational Auto Encoder ways to accurately determine anomalies from seasonal metrics occurring at

regular intervals ( i.e. daily/weekly/bi-weekly/monthly or periodic events at finer granular levels of mins/secs) so as to facilitate timely actions from the concerned team. Such timely actions help to recover from serious issues such as predictive maintenance) in the field of web applications, retail, IoT, telecom, and healthcare industry.

The metrics/KPIs that plays an important role in determining anomalies are composed of noises that are assumed to be independent, zero-mean Gaussian at every point. In fact, the seasonal KPIs comprises of seasonal patterns with local variations, and statistics of the Gaussian noises.

This article is published at https://techairesearch.com/anomaly-detection-from-head-and-abdominal-fetal-ecg-a-case-study-of-iot-anomaly-detection-using-generative-adversarial-networks/

#gan #time-series #anomaly-detection #deep-learning #data-science #machine-learning