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, is simplicity -- ...

The proposed industrial anomaly detection model is computationally efficient, memory-friendly, and also suitable for low-light conditions, common in manufacturing environments, making it well ...

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 ...

Video anomaly detection has always been a hot topic and has attracted increasing attention. Many of the existing methods for video anomaly detection depend on processing the entire video rather ...

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 ...