Abstract: Video-based anomaly detection plays a crucial role in applications like surveillance, healthcare, and autonomous systems. Deep learning techniques, such as Convolutional Neural Networks ...

ABSTRACT: The accelerating sophistication of cyberattacks poses unprecedented challenges for national security, critical infrastructures, and global digital resilience. Traditional signature-based ...

ABSTRACT: The accelerating sophistication of cyberattacks poses unprecedented challenges for national security, critical infrastructures, and global digital resilience. Traditional signature-based ...

5.1 RQ1: How does our proposed anomaly detection model perform compared to the baselines? 5.2 RQ2: How much does the sequential and temporal information within log sequences affect anomaly detection?

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

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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Abstract: The rapid expansion of data from diverse sources has made anomaly detection (AD) increasingly essential for identifying unexpected observations that may signal system failures, security ...