Insights and strategies for an autonomous vehicle with a sensor fusion innovation: A fictional outlook
A few decades ago, the idea of a car driving without human assistance was something
inconceivable. With the advent of deep learning-based machine learning in artificial …
inconceivable. With the advent of deep learning-based machine learning in artificial …
Scene-graph augmented data-driven risk assessment of autonomous vehicle decisions
There is considerable evidence that evaluating the subjective risk level of driving decisions
can improve the safety of Autonomous Driving Systems (ADS) in both typical and complex …
can improve the safety of Autonomous Driving Systems (ADS) in both typical and complex …
Deep learning-based autonomous driving systems: A survey of attacks and defenses
The rapid development of artificial intelligence, especially deep learning technology, has
advanced autonomous driving systems (ADSs) by providing precise control decisions to …
advanced autonomous driving systems (ADSs) by providing precise control decisions to …
Autonomous driving in reality with reinforcement learning and image translation
N Xu, B Tan, B Kong - arXiv preprint arXiv:1801.05299, 2018 - arxiv.org
Supervised learning is widely used in training autonomous driving vehicle. However, it is
trained with large amount of supervised labeled data. Reinforcement learning can be trained …
trained with large amount of supervised labeled data. Reinforcement learning can be trained …
Driving scenario perception-aware computing system design in autonomous vehicles
Recently, autonomous driving ignited competitions among car makers and technical
corporations. Low-level autonomous vehicles are already commercially available. However …
corporations. Low-level autonomous vehicles are already commercially available. However …
Neurall: Towards a unified visual perception model for automated driving
G Sistu, I Leang, S Chennupati… - 2019 IEEE Intelligent …, 2019 - ieeexplore.ieee.org
Convolutional Neural Networks (CNNs) are successfully used for the important automotive
visual perception tasks including object recognition, motion and depth estimation, visual …
visual perception tasks including object recognition, motion and depth estimation, visual …
Explainable artificial intelligence (XAI): An engineering perspective
The remarkable advancements in Deep Learning (DL) algorithms have fueled enthusiasm
for using Artificial Intelligence (AI) technologies in almost every domain; however, the …
for using Artificial Intelligence (AI) technologies in almost every domain; however, the …
Towards explainable semantic segmentation for autonomous driving systems by multi-scale variational attention
Explainable autonomous driving systems (EADS) are emerging recently as a combination of
explainable artificial intelligence (XAI) and vehicular automation (VA). EADS explains …
explainable artificial intelligence (XAI) and vehicular automation (VA). EADS explains …
[HTML][HTML] A review of visualisation-as-explanation techniques for convolutional neural networks and their evaluation
Visualisation techniques are powerful tools to understand the behaviour of Artificial
Intelligence (AI) systems. They can be used to identify important features contributing to the …
Intelligence (AI) systems. They can be used to identify important features contributing to the …
Explainability of Vision Transformers: A Comprehensive Review and New Perspectives
Transformers have had a significant impact on natural language processing and have
recently demonstrated their potential in computer vision. They have shown promising results …
recently demonstrated their potential in computer vision. They have shown promising results …