All Outputs (2)

Not So Robust after All: Evaluating the Robustness of Deep Neural Networks to Unseen Adversarial Attacks (2024)
Journal Article
Garaev, R., Rasheed, B., & Khan, A. M. (2024). Not So Robust after All: Evaluating the Robustness of Deep Neural Networks to Unseen Adversarial Attacks. Algorithms, 17, Article 162. https://doi.org/10.3390/a17040162

Deep neural networks (DNNs) have gained prominence in various applications, but remain vulnerable to adversarial attacks that manipulate data to mislead a DNN. This paper aims to challenge the efficacy and transferability of two contemporary defense... Read More about Not So Robust after All: Evaluating the Robustness of Deep Neural Networks to Unseen Adversarial Attacks.

Computing on Wheels: A Deep Reinforcement Learning-Based Approach (2022)
Journal Article
Ahsan Kazmi, S. M., Ho, T. M., Nguyen, T. T., Fahim, M., Khan, A., Piran, M. J., & Baye, G. (2022). Computing on Wheels: A Deep Reinforcement Learning-Based Approach. IEEE Transactions on Intelligent Transportation Systems, 23(11), 22535-22548. https://doi.org/10.1109/TITS.2022.3165662

Future generation vehicles equipped with modern technologies will impose unprecedented computational demand due to the wide adoption of compute-intensive services with stringent latency requirements. The computational capacity of the next generation... Read More about Computing on Wheels: A Deep Reinforcement Learning-Based Approach.