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 ...

Anomaly detection in images is rapidly emerging as a critical field in both industrial quality control and medical diagnostics. Leveraging deep learning techniques, researchers have developed ...

By using interactive notebooks and historical data, you can find appropriate correlations that can help you design applications that can use near-real time anomaly detection to deliver results you ...

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 ...

Anomaly detection systems are growing, mainly due to the surge in big data. How will this affect companies in the supply chain?