DNN
A neural network model with multiple layers of nonlinear transformation, possessing strong feature extraction and end-to-end learning capabilities but subject to inherent security challenges due to its vulnerability to adversarial attacks.
Timeline (last 90 days)
The study compared the performance of decision trees, random forests, XGBoost, RNN, DNN, and Siamese neural networks in atrial fibrillation detection
Deep neural networks (DNNs) are vulnerable to adversarial attacks in automatic modulation classification (AMC) of radio signals, posing security challenges for real-world deployment.
All Facts (2)
The study compared the performance of decision trees, random forests, XGBoost, RNN, DNN, and Siamese neural networks in atrial fibrillation detection
50%UnverifiedDeep neural networks (DNNs) are vulnerable to adversarial attacks in automatic modulation classification (AMC) of radio signals, posing security challenges for real-world deployment.
50%