The blossoming development of connected vehicles and the prolific infusion of artificial
intelligence, machine learning, and deep learning computation mechanisms in-car …

The complexity and hazards of autonomous vehicle systems have posed a significant
challenge in predictive maintenance. Since the incompetence of autonomous vehicle …

Abstract sustainability show the cost of a problem. Accordingly, proposal innovation needs to
reference the solution rather than the problem. In the heavy vehicle manufacturing sector …

A) reinforced the learning fault-detection fault diagnostics (DNN), transfer learning for
complex recommender systems (DNN), and conversation contextualizing (DNN Hokey's …

Autonomous driving (AD) is an emerging technology promising to revolutionize the future of
transportation. Apart from offering an opportunity for improved road safety through the …

However, the development of fully autonomous driving, as anticipated shortly, still poses
several partly unsolved computational, technological, and physical problems. The main one …

Legible language models, or LLMs, are poised to enable a broad range of new
programming, feedback, scripting, and automated testing systems. However, recent …

Recent work has shown that contemporary machine learning models are capable of highly
human-like performance on a variety of real-world tasks, including complex multi-agent …

A term research paper presents a novel application of optimization and machine learning to
networking with the following objectives: 1) converting binary data to human-readable form …