Search Results for author:
Found 4 papers, 2 papers with code
Physical Adversarial Examples for Multi-Camera Systems
Neural networks build the foundation of several intelligent systems, which, however, are known to be easily fooled by adversarial examples.
An Integrated Algorithm for Robust and Imperceptible Audio Adversarial Examples
Audio adversarial examples are audio files that have been manipulated to fool an automatic speech recognition (ASR) system, while still sounding benign to a human listener.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
R2-AD2: Detecting Anomalies by Analysing the Raw Gradient
Neural networks follow a gradient-based learning scheme, adapting their mapping parameters by back-propagating the output loss.
Semi-supervised Anomaly Detection
Supervised Anomaly Detection
$\text{A}^3$: Activation Anomaly Analysis
Based on the activation values in the target network, the alarm network decides if the given sample is normal.
Semi-supervised Anomaly Detection
Supervised Anomaly Detection
