Vision transformers have been demonstrated to yield state-of-the-art results on a variety of
computer vision tasks using attention-based networks. However, research works in …

In recent years, target detection has been widely used in specific dress detection, to reduce
the probability of accidents in certain fields such as construction sites, traffic management …

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 …

Deep learning systems, particularly those used in image classification, are threatened by
Adversarial Examples. In contrast, Adversarial Examples do not affect the mammalian visual …

Most deep neural networks (DNNs) are trained in an over-parametrized regime. In this case,
the numbers of their parameters are more than available training data which reduces the …

Recent works have shown that adversarial examples (AEs) can attack and successfully
transfer across various neural networks, highlighting the potential danger they pose …

This paper examines the impact of rain on traffic sign recognition system, addressing one of
the challenges posed by harsh environmental conditions like low lighting, extreme weather …

The rapid advancement of communication and artificial intelligence technologies is
propelling the development of connected and autonomous vehicles (CAVs), revolutionizing …

The development of Adaptive Cruise Control (ACC) systems aims to enhance the safety and
comfort of vehicles by automatically regulating the speed of the vehicle to ensure a safe gap …

Given deep neural networks' susceptibility to adversarial attacks, including adversarial
noises in the training data could improve perceived and unpredictable adversarial …