Liu, Ming

Rtfnet: Rgb-thermal fusion network for semantic segmentation of urban scenes

Sun, Y., Zuo, W., & Liu, M. (2019) · IEEE Robotics and Automation Letters

Advanced Neural Network ApplicationsAdvanced Image Fusion Techniques

Cited by 546

FuseSeg: Semantic segmentation of urban scenes based on RGB and thermal data fusion

Sun, Y., Zuo, W., Yun, P., Wang, H., & Liu, M. (2021) · IEEE Transactions on Automation Science and Engineering

Advanced Neural Network ApplicationsAdvanced Image Fusion Techniques

Cited by 270

Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems

Liu, B., Wang, L., & Liu, M. (2019) · IEEE Robotics and Automation Letters

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 242

Federated Transfer Reinforcement Learning for Autonomous Driving

Liang, X., Liu, Y., Chen, T., Liu, M., & Yang, Q. (2019) · arXiv

Reinforcement Learning in RoboticsAutonomous Vehicle Technology and Safety

Cited by 131

VR-Goggles for Robots: Real-to-Sim Domain Adaptation for Visual Control

Zhang, J., Tai, L., Yun, P., Xiong, Y., Liu, M., Boedecker, J., & Burgard, W. (2019) · IEEE Robotics and Automation Letters

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 109

Flexible and fully implantable upconversion device for wireless optogenetic stimulation of the spinal cord in behaving animals

Wang, Y., Xie, K., Yue, H., Chen, X., Luo, X., Liao, Q., Liu, M., Wang, F., & Shi, P. (2020) · Nanoscale

Neuroscience and Neural EngineeringLuminescence Properties of Advanced Materials

Cited by 42