Anomaly detection is a powerful technique for identifying unexpected patterns in data and can provide valuable insights for many applications. However, it is important to carefully consider the ...

Abstract: Real-time anomaly detection of slab thickness is essential for ensuring quality in continuous casting. Existing methods face challenges in data preprocessing and real-time monitoring. This ...

This repo construct various Graph Autoencoders (with and without attention) for model-agnostic anomaly detection at particle collisions. It's currently set up to work out of the box using the LHC ...

For an autoencoder anomaly detection system, model overfitting is characterized by a situation where all reconstructed inputs match the source inputs very closely, and therefore all reconstruction ...

SHENZHEN, China - MicroCloud Hologram Inc. (NASDAQ: HOLO), a global provider of holographic technology services with a market capitalization of $28.76 million, has announced the optimization of its ...

The autoencoder algorithm achieved the best anomaly detection performance than the other benchmark techniques. Compared with the LOF algorithm, which has the best results among the traditional ...

For an autoencoder anomaly detection system, model overfitting is characterized by a situation where all reconstructed inputs match the source inputs very closely, and therefore all reconstruction ...