Traffic sign recognition is an essential component of perception in autonomous vehicles,
which is currently performed almost exclusively with deep neural networks (DNNs) …

To better understand the road condition and make correct driving decisions, traffic sign
recognition becomes a crucial component commonly equipped in the vision system of …

Real-world traffic sign recognition is an important step toward building autonomous vehicles,
most of which highly dependent on deep neural networks (DNNs). Recent studies …

Deep Neural Networks (DNNs) are increasingly applied in the real world in safety critical
applications like advanced driver assistance systems. An example for such use case is …

Deep neural networks are found to be vulnerable to adversarial examples. These
drawbacks can cause the security problem of machine vision systems. For automated …

Recent adversarial attacks with real world applications are capable of deceiving deep
neural networks (DNN), which often appear as printed stickers applied to objects in physical …

Adversarial attacks can make deep neural network (DNN) models predict incorrect output
labels, such as misclassified traffic signs, for autonomous vehicle (AV) perception modules …

Autonomous driving systems (ADS) can instantaneously and accurately recognize traffic
signs by using deep neural networks (DNNs). Although adversarial attacks are well-known …

Sign recognition is an integral part of autonomous cars. Any misclassification of traffic signs
can potentially lead to a multitude of disastrous consequences, ranging from a life …

Recent work show that Deep Neural Networks (DNNs) have created great performance in
many tasks, but they are vulnerable to adversarial examples which trigger Artificial …