That challenge is examined in the study Towards Eco-Friendly Cybersecurity: Machine Learning-Based Anomaly Detection with ...

Anomaly detection in the context of data science is detecting a data sample that is out of the ordinary and does not fit into the general data pattern (or an outlier). This deviation can result from a ...

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

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-suited ...

In the vast and ever-evolving realm of cybersecurity, the need for robust defense mechanisms has never been more pressing. With cyber threats growing in sophistication and frequency, organizations ...

A recent Physical Review Letters publication presents a thorough analysis of MicroBooNE detector data, investigating the anomalous surplus of neutrino-like events detected by the preceding MiniBooNE ...