… of autonomous driving. The … and deep learning technologies used in autonomous driving,
and provide a survey on state-of-the-art deep learning and AI methods applied to self-driving …

… autonomous driving (AD), improving driving safety while minimizing the efforts of human
drivers with the help of advanced artificial intelligence (AI) techniques. Recently, deep learning (…

… This document also defines the important terms related to Autonomous driving Architecture,
which include: Dynamic Driving Task (DDT): “Very of the actual working and tactical …

… Hence, this paper will explain how deep learning is … for autonomous driving (such as object
detection and semantic segmentation) is in progress. This paper explains how deep learning …

Autonomous driving requires reliable and accurate detection and recognition of surrounding
objects in real drivable environments. Although different object detection algorithms have …

… learning-based adversarial attacks. Inevitably, the safety and security of deep learning-based
autonomous driving … adversarial attacks for various deep learning models and attacks in …

… In 2019, the fathers of deep learning, Hinton, Bengio and … has seen rapid developments of
deep learning techniques with … we investigate how autonomous driving marries deep learning. …

… tasks for autonomous driving using DL techniques. … -D object detection applied for autonomous
driving are concluded. … clouds in the field of autonomous driving for specific tasks, such …

… deep learning based algorithm for autonomous driving, and we refer to our algorithm as
GoogLenet for Autonomous Driving … unrealistic assumptions about the autonomous vehicle or its …

… Most recently, deep learning-based approaches have become … of-the-art of deep
learning-based approaches for vehicle behavior … of these input data in autonomous driving …