Abstract: The current fast proliferation of the Internet of Things (IoT) networks has made anomaly detection and security more difficult. Traditional methods are not able to detect hostile activities ...
Congress’ latest bills look to apply AI for both public benefit and enhanced federal operations, namely safeguarding AI ...
When AI-driven detection underperforms, the instinct is to tune the algorithm, retrain the model or push the vendor for a ...
Genomic surveillance—the process of monitoring and sequencing pathogens—is one of the most important tools for detecting ...
Principal Data Engineer Rajesh Mattaparthi is using transformer-based AI to detect hidden faults in standby power generators ...
PatchCore is a widely used algorithm for industrial anomaly detection, due to its high performance compared to alternative approaches. This paper focuses on optimizing its architecture for the ...
AI's role in data centers enhances operational efficiency, predictive maintenance, and cybersecurity, paving the way for ...
This project provides a comprehensive RESTful API for detecting anomalies in financial transactions using statistical process control methods. Built with .NET 9 and following clean architecture ...
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