Spatio-temporal context graph transformer design for map-free multi-agent trajectory prediction
Z Wang, J Zhang, J Chen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Predicting the motion of surrounding vehicles is an important function of autonomous
vehicles. However, most of the current state-of-the-art trajectory prediction models rely …
vehicles. However, most of the current state-of-the-art trajectory prediction models rely …
Density-Adaptive Model Based on Motif Matrix for Multi-Agent Trajectory Prediction
Multi-agent trajectory prediction is essential in autonomous driving risk avoidance and traffic
flow control. However the heterogeneous traffic density on interactions which caused by …
flow control. However the heterogeneous traffic density on interactions which caused by …
Hierarchical Autoencoder Frequency Features for Stress Detection
R Kuttala, R Subramanian, VRM Oruganti - IEEE Access, 2023 - ieeexplore.ieee.org
Stress has a significant negative impact on people, which has made it a primary social
concern. Early stress detection is essential for effective stress management. This study …
concern. Early stress detection is essential for effective stress management. This study …
UMT-net: A uniform multi-task network with adaptive task weighting
This article introduces a versatile multi-task learning framework (UMT-Net) and an adaptive
task weighting (ATW) training method, specifically designed for resource-constrained …
task weighting (ATW) training method, specifically designed for resource-constrained …