New Study on Synthetic Data-Driven Sub-surface Anomaly Detection by VE3 AI Research

VE3 AI Research publishes a study on synthetic data, magnetic dipole modeling, and unsupervised AI for scalable anomaly ...
Nature

A lightweight anomaly detection model for network traffic using multi scale spatio temporal residual learning

With the continuous upgrading of network attacks, network abnormal traffic detection has become a key technology to ensure network security. However, existing detection methods still face challenges ...
Nature

Magnetic Anomaly Detection Techniques and Applications

Magnetic anomaly detection encompasses a suite of methods for identifying disruptions in the Earth’s ambient magnetic field caused by ferromagnetic objects or geological structures. Fundamental ...
Visual Studio Magazine

DBSCAN Clustering and Anomaly Detection Using C#

A good way to see where this article is headed is to take a look at the screenshot in Figure 1 and the graph in Figure 2. The demo program begins by loading a tiny 10-item dataset into memory. The ...
Washington Technology

GDIT forms partnership with commercial quantum computing firm

General Dynamics IT's pact with IonQ will focus on areas such as geospatial and sensor data processing, fraud detection, and health research. General Dynamics' IT services unit has formed a strategic ...