Artificial Intelligence in Autonomous Vehicles—A Survey of Trends and Challenges

U Rajasekaran, A Malini… - Artificial Intelligence for …, 2024 - Wiley Online Library
The potential for connected automated vehicles is multifaceted, and automated
advancement deals with more of Internet of Things (IoTs) development enabling artificial …

Transfer learning for galaxy feature detection: Finding giant star-forming clumps in low-redshift galaxies using Faster Region-based Convolutional Neural Network

JJ Popp, H Dickinson, S Serjeant… - RAS Techniques …, 2024 - academic.oup.com
Giant star-forming clumps (GSFCs) are areas of intensive star-formation that are commonly
observed in high-redshift (z≳ 1) galaxies but their formation and role in galaxy evolution …

A Traffic Sign Classification Method using LiDAR Corrected Intensity and Geometric Feature

X Li, R Yu, T Bi, L Xu - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
As an important perception sensor for autonomous vehicles (AVs), light detection and
ranging (LiDAR) provides 3D-spatial and 1D-intensity information. To boost the ability of …

Enhancing Autonomous Vehicle Design and Testing: A Comprehensive Review of AR and VR Integration

E Ejichukwu, L Tong, G Hazime, B Jia - arXiv preprint arXiv:2404.19021, 2024 - arxiv.org
This comprehensive literature review explores the potential of Augmented Reality and
Virtual Reality technologies to enhance the design and testing of autonomous vehicles. By …

A Comprehensive Review of Machine Learning Approaches for Detecting Malicious Software.

L Yuanming, R Latih - International Journal on Advanced …, 2024 - search.ebscohost.com
With the continuous development of technology, the types of malware and their variants
continue to increase, which has become an enormous challenge to network security. These …

MFMAN-YOLO: A Method for Detecting Pole-like Obstacles in Complex Environment

L Cai, H Wang, C Zhou, Y Wang, B Liu - arXiv preprint arXiv:2307.12548, 2023 - arxiv.org
In real-world traffic, there are various uncertainties and complexities in road and weather
conditions. To solve the problem that the feature information of pole-like obstacles in …

Evolutionary Image Quality Monitoring for ADAS under Adverse Weather

JD González, M Maehlisch - 2024 IEEE Intelligent Vehicles …, 2024 - ieeexplore.ieee.org
This work presents a method for monitoring the quality of the data captured by the cameras
of an Advanced Driver Assistance System or an Autonomous Driving vehicle. Adverse …

A Modular Deep Learning Framework for Scene Understanding in Augmented Reality Applications

V Li, B Villarini, JC Nebel… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Taking as input natural images and videos, augmented reality (AR) applications aim to
enhance the real world with superimposed digital contents, enabling interaction between the …

A Study to Investigate the Role and Challenges Associated to the Use of Deep Learning in Autonomous Vehicles

NO Aljehane - 2024 - preprints.org
The application of deep learning in autonomous vehicles has surged over the years with the
advances in technologies. This research explores the integration of deep learning …

[HTML][HTML] Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidance

Q Yuan, Y Gao, J Zhu, H Xiong, Q Xu… - Digital Transportation …, 2023 - maxapress.com
With the development of intelligent vehicles and autonomous driving technology, the safety
of vulnerable road user (VRU) in traffic has been more guaranteed, and many research …