48 citations · 65 across the 5 of their papers we have counts for
5 papers
OptiPMB: Enhancing 3D Multi-Object Tracking with Optimized Poisson Multi-Bernoulli Filtering
Guanhua Ding, Yuxuan Xia, Runwei Guan +5
Accurate 3D multi-object tracking (MOT) is crucial for autonomous driving, as it enables robust perception, navigation, and planning in complex environments. While deep learning-ba…
Responsible Federated Learning in Smart Transportation: Outlooks and Challenges
Xiaowen Huang, Tao Huang, Shushi Gu +2
Integrating artificial intelligence (AI) and federated learning (FL) in smart transportation has raised critical issues regarding their responsible use. Ensuring responsible AI is…
Vehicle-to-Everything Cooperative Perception for Autonomous Driving
Tao Huang, Jianan Liu, Xi Zhou +5
Achieving fully autonomous driving with enhanced safety and efficiency relies on vehicle-to-everything cooperative perception, which enables vehicles to share perception data, ther…
Localization-Guided Track: A Deep Association Multi-Object Tracking Framework Based on Localization Confidence of Detections
Ting Meng, Chunyun Fu, Mingguang Huang +4
In currently available literature, no tracking-by-detection (TBD) paradigm-based tracking method has considered the localization confidence of detection boxes. In most TBD-based me…
Performance of a GPU- and Time-Efficient Pseudo 3D Network for Magnetic Resonance Image Super-Resolution and Motion Artifact Reduction
Hao Li, Jianan Liu, Marianne Schell +8
Shortening acquisition time and reducing motion artifacts are the most critical challenges in magnetic resonance imaging (MRI). Deep learning-based image restoration has emerged as…