This works shows a comparison of two architectures of DBN (Deep Belief Networks) and a FFNN (Feed Forward Neural Network), stressing on understanding how DBNs work. Their robustness to noise and adversarial attacks is also tested.
Comparison of DBNs and FFNN, stressing on understanding how DBNs work and how robust they are against noise and adversarial attacks.
This works shows a comparison of two architectures of DBN (Deep Belief Networks) and a FFNN (Feed Forward Neural Network), stressing on understanding how DBNs work. Their robustness to noise and adversarial attacks is also tested.
Comparison of DBNs and FFNN, stressing on understanding how DBNs work and how robust they are against noise and adversarial attacks.