The main advantage of using PCA for anomaly detection, compared to alternative techniques such as a neural autoencoder, is simplicity -- assuming you have a function that computes eigenvalues and ...

Applying anomaly detection to embedded systems is a challenge, but it's one that can provide benefits like identifying a device that's not working properly or one that might be under attack by ...

In this study, we explore an image-based method to automate the manual anomaly detection process on quality control plots using deep learning. To do this we trained a Convolutional Neural Network (CNN ...

The Data Science Lab Anomaly Detection Using Principal Component Analysis (PCA) The main advantage of using PCA for anomaly detection, compared to alternative techniques such as a neural autoencoder, ...