Abstract: Hyperspectral anomaly detection (HAD) aims to recognize a minority of anomalies that are spectrally different from their surrounding background without prior knowledge. Deep neural networks ...
Abstract: Automated detection of software vulnerabilities is critical for enhancing security, yet existing methods often struggle with the complexity and diversity of modern codebases. In this paper, ...
RF jamming detection system using a lightweight 2D CNN architecture that operates on Mel spectrograms derived from RSSI signals. This research demonstrates both the promise and critical limitations of ...
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