Much research on Machine Learning testing relies on empirical studies th...
Natural Language Processing (NLP) models based on Machine Learning (ML) ...
While leveraging additional training data is well established to improve...
Vulnerability to adversarial attacks is a well-known weakness of Deep Ne...
While the literature on security attacks and defense of Machine Learning...
The generation of feasible adversarial examples is necessary for properl...
Vulnerability to adversarial attacks is a well-known weakness of Deep Ne...
The rapid spread of the Coronavirus SARS-2 is a major challenge that led...
We propose adversarial embedding, a new steganography and watermarking
t...
Deep Neural Networks (DNNs) are intensively used to solve a wide variety...