158 citations · 170 across the 6 of their papers we have counts for
6 papers
Advancing from Automated to Autonomous Beamline by Leveraging Computer Vision
Baolu Li, Hongkai Yu, Huiming Sun +4
The synchrotron light source, a cutting-edge large-scale user facility, requires autonomous synchrotron beamline operations, a crucial technique that should enable experiments to b…
Domain Adaptation based Object Detection for Autonomous Driving in Foggy and Rainy Weather
Jinlong Li, Runsheng Xu, Xinyu Liu +5
Typically, object detection methods for autonomous driving that rely on supervised learning make the assumption of a consistent feature distribution between the training and testin…
RXFOOD: Plug-in RGB-X Fusion for Object of Interest Detection
Jin Ma, Jinlong Li, Qing Guo +3
The emergence of different sensors (Near-Infrared, Depth, etc.) is a remedy for the limited application scenarios of traditional RGB camera. The RGB-X tasks, which rely on RGB inpu…
Deep Transfer Learning for Intelligent Vehicle Perception: a Survey
Xinyu Liu, Jinlong Li, Jin Ma +4
Deep learning-based intelligent vehicle perception has been developing prominently in recent years to provide a reliable source for motion planning and decision making in autonomou…
Learning for Vehicle-to-Vehicle Cooperative Perception under Lossy Communication
Jinlong Li, Runsheng Xu, Xinyu Liu +4
Deep learning has been widely used in the perception (e.g., 3D object detection) of intelligent vehicle driving. Due to the beneficial Vehicle-to-Vehicle (V2V) communication, the d…
Domain Adaptive Object Detection for Autonomous Driving under Foggy Weather
Jinlong Li, Runsheng Xu, Jin Ma +3
Most object detection methods for autonomous driving usually assume a consistent feature distribution between training and testing data, which is not always the case when weathers…