In recent years, artificial intelligence technologies have been widely used in computer
vision, natural language processing, automatic driving, and other fields. However, artificial …

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 (DNN) have achieved unprecedented success in numerous machine
learning tasks in various domains. However, the existence of adversarial examples leaves …

Enabling autonomous driving (AD) can be considered one of the biggest challenges in
today? s technology. AD is a complex task accomplished by several functionalities, with …

Connected and autonomous vehicles (CAV aka driverless cars) offset human response for
transportation infrastructure, enhancing traffic efficiency, travel leisure, and road safety …

Autonomous vehicles (AVs) heavily depend on machine learning-based algorithms for the
purpose of environmental perception. However, extensively utilized deep learning-based …

Adversarial examples represent a serious threat for deep neural networks in several
application domains and a huge amount of work has been produced to investigate them and …

Deep neural networks have been widely used in various downstream tasks, especially those
safety-critical scenario such as autonomous driving, but deep networks are often threatened …

Object detection is considered as one of the most important applications of deep learning.
However, the object detection techniques lose their effectiveness and reliability when they …

Deep neural networks (DNNs) are being incorporated into various autonomous systems like
self-driving cars and robots. However, there is a rising concern about the robustness of …