Review and perspectives on driver digital twin and its enabling technologies for intelligent vehicles
Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving
and transportation systems to digitize and synergize connected automated vehicles …
and transportation systems to digitize and synergize connected automated vehicles …
[HTML][HTML] Toward human-in-the-loop AI: Enhancing deep reinforcement learning via real-time human guidance for autonomous driving
Due to its limited intelligence and abilities, machine learning is currently unable to handle
various situations thus cannot completely replace humans in real-world applications …
various situations thus cannot completely replace humans in real-world applications …
Uncertainty-aware model-based reinforcement learning: Methodology and application in autonomous driving
To further improve learning efficiency and performance of reinforcement learning (RL), a
novel uncertainty-aware model-based RL method is proposed and validated in autonomous …
novel uncertainty-aware model-based RL method is proposed and validated in autonomous …
A hybrid attention-based paralleled deep learning model for tool wear prediction
J Duan, X Zhang, T Shi - Expert Systems with Applications, 2023 - Elsevier
In modern manufacturing process, tool condition significantly affects work efficiency,
machinery downtime and operating profit. Convolutional neural network (CNN), recurrent …
machinery downtime and operating profit. Convolutional neural network (CNN), recurrent …
Driver anomaly quantification for intelligent vehicles: A contrastive learning approach with representation clustering
Driver anomaly quantification is a fundamental capability to support human-centric driving
systems of intelligent vehicles. Existing studies usually treat it as a classification task and …
systems of intelligent vehicles. Existing studies usually treat it as a classification task and …
Potential future directions in optimization of students' performance prediction system
Previous studies widely report the optimization of performance predictions to highlight at‐
risk students and advance the achievement of excellent students. They also have …
risk students and advance the achievement of excellent students. They also have …
[Retracted] Human Resource Demand Prediction and Configuration Model Based on Grey Wolf Optimization and Recurrent Neural Network
NK Rajagopal, M Saini, R Huerta-Soto… - Computational …, 2022 - Wiley Online Library
Business development is dependent on a well‐structured human resources (HR) system
that maximizes the efficiency of an organization's human resources input and output. It is …
that maximizes the efficiency of an organization's human resources input and output. It is …
Sign language recognition for Arabic alphabets using transfer learning technique
M Zakariah, YA Alotaibi, D Koundal… - Computational …, 2022 - Wiley Online Library
Sign language is essential for deaf and mute people to communicate with normal people
and themselves. As ordinary people tend to ignore the importance of sign language, which …
and themselves. As ordinary people tend to ignore the importance of sign language, which …
An effective MBSE approach for constructing industrial robot digital twin system
X Zhang, B Wu, X Zhang, J Duan, C Wan… - Robotics and Computer …, 2023 - Elsevier
Recently, the rapid development of digital twin (DT) technology has been regarded
significant in Cyber-physical systems (CPS) promotion. Scholars are focusing on the …
significant in Cyber-physical systems (CPS) promotion. Scholars are focusing on the …
Translution-SNet: A semisupervised hyperspectral image stripe noise removal based on transformer and CNN
C Wang, M Xu, Y Jiang, G Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Hyperspectral remote sensing images (HSIs) have been applied in urban planning,
environmental monitoring, and other fields. However, they are susceptible to noise …
environmental monitoring, and other fields. However, they are susceptible to noise …