Industrial anomaly detection is hindered by data inefficiency and dependence on large-scale training sets. We introduce CLIP-FSQAE, a novel framework for few-shot anomaly detection that integrates ...

The natural gas pipeline network has a complex topology with variable flow directions, and the supply demand relationships between nodes exhibit cyclical, fluctuating, and time-varying trends.

This integrated engine aggregates multiple data sources and deploys cutting-edge machine learning and anomaly detection algorithms to create a powerful signal to detect fraud.

AI-trained data analysis models may offer a more rapid and accurate detection of a range of neurologic conditions, including those involving motor function such as Parkinson’s disease and normal ...

Autoencoder-based SCADA Telemetry Anomaly Detection This project implements an autoencoder-based anomaly detection system for SCADA (Supervisory Control and Data Acquisition) telemetry data. The ...

Utilities are cautiously embracing AI for predictive maintenance and fieldwork support as data centers and climate change strain the energy grid.

After the whole lava bridge debacle and heading into Act 2, you and your Jan Scientist alter will have gotten to know each other better in The Alters.

This paper proposes a novel approach using the Noisy-Student technique for anomaly detection. It addresses data contamination by combining a density-estimation teacher model for pseudo-labeling with a ...

With no way to stop the onslaught of AI music, the industry is taking a different approach: figuring out how to make money off of it.