108 citations · 330 across the 34 of their papers we have counts for
35 papers
Distributed Neurodynamics-Based Backstepping Optimal Control for Robust Constrained Consensus of Underactuated Underwater Vehicles Fleet
Tao Yan, Zhe Xu, Simon X. Yang +1
Robust constrained formation tracking control of underactuated underwater vehicles (UUVs) fleet in three-dimensional space is a challenging but practical problem. To address this p…
Distributed Robust Learning-Based Backstepping Control Aided with Neurodynamics for Consensus Formation Tracking of Underwater Vessels
Tao Yan, Zhe Xu, Simon X. Yang
This paper addresses distributed robust learning-based control for consensus formation tracking of multiple underwater vessels, in which the system parameters of the marine vessels…
You've Got Two Teachers: Co-evolutionary Image and Report Distillation for Semi-supervised Anatomical Abnormality Detection in Chest X-ray
Jinghan Sun, Dong Wei, Zhe Xu +4
Chest X-ray (CXR) anatomical abnormality detection aims at localizing and characterising cardiopulmonary radiological findings in the radiographs, which can expedite clinical workf…
Data-Driven Model Discrimination of Switched Nonlinear Systems with Temporal Logic Inference
Zeyuan Jin, Nasim Baharisangari, Zhe Xu +1
This paper addresses the problem of data-driven model discrimination for unknown switched systems with unknown linear temporal logic (LTL) specifications, representing tasks, that…
Distributed Leader Follower Formation Control of Mobile Robots based on Bioinspired Neural Dynamics and Adaptive Sliding Innovation Filter
Zhe Xu, Tao Yan, Simon X. Yang +1
This paper investigated the distributed leader follower formation control problem for multiple differentially driven mobile robots. A distributed estimator is first introduced and…
Human-machine Interactive Tissue Prototype Learning for Label-efficient Histopathology Image Segmentation
Wentao Pan, Jiangpeng Yan, Hanbo Chen +4
Recently, deep neural networks have greatly advanced histopathology image segmentation but usually require abundant annotated data. However, due to the gigapixel scale of whole sli…
Distributed Differentially Private Control Synthesis for Multi-Agent Systems with Metric Temporal Logic Specifications
Nasim Baharisangari, Zhe Xu
In this paper, we propose a distributed differentially private receding horizon control (RHC) approach for multi-agent systems (MAS) with metric temporal logic (MTL) specifications…
A Hybrid Tracking Control Strategy for an Unmanned Underwater Vehicle Aided with Bioinspired Neural Dynamics
Zhe Xu, Tao Yan, Simon X. Yang +1
Tracking control has been a vital research topic in robotics. This paper presents a novel hybrid control strategy for an unmanned underwater vehicle (UUV) based on a bioinspired ne…
Non-Parametric Neuro-Adaptive Formation Control
Christos K. Verginis, Zhe Xu, Ufuk Topcu
We develop a learning-based algorithm for the distributed formation control of networked multi-agent systems governed by unknown, nonlinear dynamics. Most existing algorithms eithe…
Deformer: Towards Displacement Field Learning for Unsupervised Medical Image Registration
Jiashun Chen, Donghuan Lu, Yu Zhang +5
Recently, deep-learning-based approaches have been widely studied for deformable image registration task. However, most efforts directly map the composite image representation to s…
Consensus Formation Tracking for Multiple AUV Systems Using Distributed Bioinspired Sliding Mode Control
Tao Yan, Zhe Xu, Simon X. Yang
Consensus formation tracking of multiple autonomous underwater vehicles (AUVs) subject to nonlinear and uncertain dynamics is a challenging problem in robotics. To tackle this chal…
Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction
Jiangpeng Yan, Chenghui Yu, Hanbo Chen +4
Recently, deep neural networks have greatly advanced undersampled Magnetic Resonance Image (MRI) reconstruction, wherein most studies follow the one-anatomy-one-network fashion, i.…
Double-Uncertainty Guided Spatial and Temporal Consistency Regularization Weighting for Learning-based Abdominal Registration
Zhe Xu, Jie Luo, Donghuan Lu +7
In order to tackle the difficulty associated with the ill-posed nature of the image registration problem, regularization is often used to constrain the solution space. For most lea…
Trust It or Not: Confidence-Guided Automatic Radiology Report Generation
Yixin Wang, Zihao Lin, Zhe Xu +7
Medical imaging plays a pivotal role in diagnosis and treatment in clinical practice. Inspired by the significant progress in automatic image captioning, various deep learning (DL)…
Unsupervised Multimodal Image Registration with Adaptative Gradient Guidance
Zhe Xu, Jiangpeng Yan, Jie Luo +2
Multimodal image registration (MIR) is a fundamental procedure in many image-guided therapies. Recently, unsupervised learning-based methods have demonstrated promising performance…
Unimodal Cyclic Regularization for Training Multimodal Image Registration Networks
Zhe Xu, Jiangpeng Yan, Jie Luo +3
The loss function of an unsupervised multimodal image registration framework has two terms, i.e., a metric for similarity measure and regularization. In the deep learning era, rese…
Real-time and Large-scale Fleet Allocation of Autonomous Taxis: A Case Study in New York Manhattan Island
Yue Yang, Wencang Bao, Mohsen Ramezani +1
Nowadays, autonomous taxis become a highly promising transportation mode, which helps relieve traffic congestion and avoid road accidents. However, it hinders the wide implementati…
F3RNet: Full-Resolution Residual Registration Network for Deformable Image Registration
Zhe Xu, Jie Luo, Jiangpeng Yan +2
Deformable image registration (DIR) is essential for many image-guided therapies. Recently, deep learning approaches have gained substantial popularity and success in DIR. Most dee…
Adversarial Uni- and Multi-modal Stream Networks for Multimodal Image Registration
Zhe Xu, Jie Luo, Jiangpeng Yan +4
Deformable image registration between Computed Tomography (CT) images and Magnetic Resonance (MR) imaging is essential for many image-guided therapies. In this paper, we propose a…
Reward Machines for Cooperative Multi-Agent Reinforcement Learning
Cyrus Neary, Zhe Xu, Bo Wu +1
In cooperative multi-agent reinforcement learning, a collection of agents learns to interact in a shared environment to achieve a common goal. We propose the use of reward machines…
Active Finite Reward Automaton Inference and Reinforcement Learning Using Queries and Counterexamples
Zhe Xu, Bo Wu, Aditya Ojha +2
Despite the fact that deep reinforcement learning (RL) has surpassed human-level performances in various tasks, it still has several fundamental challenges. First, most RL methods…
Distributed Policy Synthesis of Multi-Agent Systems With Graph Temporal Logic Specifications
Murat Cubuktepe, Zhe Xu, Ufuk Topcu
We study the distributed synthesis of policies for multi-agent systems to perform \emph{spatial-temporal} tasks. We formalize the synthesis problem as a \emph{factored} Markov deci…
Robust Inference and Verification of Temporal Logic Classifier-in-the-loop Systems
Zhe Xu
Autonomous systems embedded with machine learning modules often rely on deep neural networks for classifying different objects of interest in the environment or different actions o…
Policy Synthesis for Factored MDPs with Graph Temporal Logic Specifications
Murat Cubuktepe, Zhe Xu, Ufuk Topcu
We study the synthesis of policies for multi-agent systems to implement spatial-temporal tasks. We formalize the problem as a factored Markov decision process subject to so-called…