There's plenty of buzz around how AI can make self-healing networks a reality -- but how close are we to that, really?
That challenge is examined in the study Towards Eco-Friendly Cybersecurity: Machine Learning-Based Anomaly Detection with ...
Demos include PC-based and FS42 camera-based deep learning optical character recognition, deep learning anomaly detection on the newly launched Zebra NS42 camera (Credit: Zebra) Machine vision, edge ...
Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...
The mathematics protecting communications since before the internet remain our strongest defense against machine-speed ...
Abstract: Credit card fraud detection presents a significant challenge due to the extreme class imbalance in transaction datasets. Traditional machine learning models struggle to achieve high recall ...
Abstract: With the widespread adoption of Healthcare Internet of Things devices, the need for effective intrusion and anomaly detection has become pivotal in ensuring network security. However, the ...
Welcome to the Open-Source Benchmark of Anomaly Detection (OSBAD) repository, a unified, reproducible framework for evaluating the performance of various statistical, distance-based, and machine ...
Introduction: Recent advances in artificial intelligence have created opportunities for medical anomaly detection through multimodal learning frameworks. However, traditional systems struggle to ...
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