Autonomous driving has achieved significant milestones in research and development over
the last two decades. There is increasing interest in the field as the deployment of …

This survey reviews explainability methods for vision-based self-driving systems trained with
behavior cloning. The concept of explainability has several facets and the need for …

The automotive industry has witnessed an increasing level of development in the past
decades; from manufacturing manually operated vehicles to manufacturing vehicles with a …

Nowadays, deep vision models are being widely deployed in safety-critical applications, eg,
autonomous driving, and explainability of such models is becoming a pressing concern …

Connected autonomous vehicles (CAVs) are revolutionizing the development of
transportation due to their potential to improve transportation performance in many ways …

With the level of automation increases in vehicles, such as conditional and highly automated
vehicles (AVs), drivers are becoming increasingly out of the control loop, especially in …

As deep learning models are increasingly used in safety-critical applications, explainability
and trustworthiness become major concerns. For simple images, such as low-resolution face …

The remarkable advancements in Deep Learning (DL) algorithms have fueled enthusiasm
for using Artificial Intelligence (AI) technologies in almost every domain; however, the …

In recent years, the advancement of deep-learning technologies has greatly promoted the
research progress of autonomous driving. However, deep neural network is like a black box …

Generative AI models for music and the arts in general are increasingly complex and hard to
understand. The field of explainable AI (XAI) seeks to make complex and opaque AI models …