All Outputs (99)

ResDO-UNet: A deep residual network for accurate retinal vessel segmentation from fundus images (2022)
Journal Article
Liu, Y., Shen, J., Yang, L., Bian, G., & Yu, H. (2023). ResDO-UNet: A deep residual network for accurate retinal vessel segmentation from fundus images. Biomedical Signal Processing and Control, 79, Article 104087. https://doi.org/10.1016/j.bspc.2022.1040

For the clinical diagnosis, it is essential to obtain accurate morphology data of retinal blood vessels from patients, and the morphology of retinal blood vessels can well help doctors to judge the patient’s condition and give targeted therapeutic me... Read More about ResDO-UNet: A deep residual network for accurate retinal vessel segmentation from fundus images.

Event-Triggered Distributed Data-Driven Iterative Learning Bipartite Formation Control for Unknown Nonlinear Multiagent Systems (2022)
Journal Article
Zhao, H., Yu, H., & Peng, L. (2024). Event-Triggered Distributed Data-Driven Iterative Learning Bipartite Formation Control for Unknown Nonlinear Multiagent Systems. IEEE Transactions on Neural Networks and Learning Systems, 35(1), 417-427. https://doi.or

In this study, we investigate the event-triggering time-varying trajectory bipartite formation tracking problem for a class of unknown nonaffine nonlinear discrete-time multiagent systems (MASs). We first obtain an equivalent linear data model with a... Read More about Event-Triggered Distributed Data-Driven Iterative Learning Bipartite Formation Control for Unknown Nonlinear Multiagent Systems.

Learning-based Robust Bipartite Consensus Control for a Class of Multiagent Systems (2022)
Journal Article
Zhao, H., Shan, J., Peng, L., & Yu, H. (2023). Learning-based Robust Bipartite Consensus Control for a Class of Multiagent Systems. IEEE Transactions on Industrial Electronics, 70(4), 4068-4076. https://doi.org/10.1109/tie.2022.3174275

This paper studies the robust bipartite consensus problems for heterogeneous nonlinear nonaffine discrete-time multi-agent systems (MASs) with fixed and switching topologies against data dropout and unknown disturbances. At first, the controlled syst... Read More about Learning-based Robust Bipartite Consensus Control for a Class of Multiagent Systems.

Using Deep Neural Networks to Classify Symbolic Road Markings for Autonomous Vehicles (2022)
Journal Article
Suarez-Mash, D., Ghani, A., See, C. H., Keates, S., & Yu, H. (2022). Using Deep Neural Networks to Classify Symbolic Road Markings for Autonomous Vehicles. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 9(31), Article e2. https:

To make autonomous cars as safe as feasible for all road users, it is essential to interpret as many sources of trustworthy information as possible. There has been substantial research into interpreting objects such as traffic lights and pedestrian i... Read More about Using Deep Neural Networks to Classify Symbolic Road Markings for Autonomous Vehicles.

Accelerated Diagnosis of Novel Coronavirus (COVID-19)—Computer Vision with Convolutional Neural Networks (CNNs) (2022)
Journal Article
Ghani, A., Aina, A., See, C. H., Yu, H., & Keates, S. (2022). Accelerated Diagnosis of Novel Coronavirus (COVID-19)—Computer Vision with Convolutional Neural Networks (CNNs). Electronics, 11(7), Article 1148. https://doi.org/10.3390/electronics11071148

Early detection and diagnosis of COVID-19, as well as exact separation of non-COVID-19 cases in a non-invasive manner in the earliest stages of the disease, are critical concerns in the current COVID-19 pandemic. Convolutional Neural Network (CNN) ba... Read More about Accelerated Diagnosis of Novel Coronavirus (COVID-19)—Computer Vision with Convolutional Neural Networks (CNNs).

Distributed Event-triggered Bipartite Consensus for Multi-agent Systems Against Injection Attacks (2022)
Journal Article
Zhao, H., Shan, J., Peng, L., & Yu, H. (2023). Distributed Event-triggered Bipartite Consensus for Multi-agent Systems Against Injection Attacks. IEEE Transactions on Industrial Informatics, 19(4), 5377-5386. https://doi.org/10.1109/tii.2022.3157595

This paper studies fully distributed data-driven problems for nonlinear discrete-time multi-agent systems (MASs) with fixed and switching topologies preventing injection attacks. We first develop an enhanced compact form dynamic linearization model b... Read More about Distributed Event-triggered Bipartite Consensus for Multi-agent Systems Against Injection Attacks.

A novel dynamic gesture understanding algorithm fusing convolutional neural networks with hand-crafted features (2022)
Journal Article
Liu, A., Song, S., Yang, L., Bian, G., & Yu, H. (2022). A novel dynamic gesture understanding algorithm fusing convolutional neural networks with hand-crafted features. Journal of Visual Communication and Image Representation, 83, Article 103454. https://

Dynamic gestures have attracted much attention in recent years due to their user-friendly interactive characteristics. However, accurate and efficient dynamic gesture understanding remains a challenge due to complex scenarios and motion information.... Read More about A novel dynamic gesture understanding algorithm fusing convolutional neural networks with hand-crafted features.

Human Gait Data Augmentation and Trajectory Prediction for Lower-Limb Rehabilitation Robot Control Using GANs and Attention Mechanism (2021)
Journal Article
Wang, Y., Li, Z., Wang, X., Yu, H., Liao, W., & Arifoglu, D. (2021). Human Gait Data Augmentation and Trajectory Prediction for Lower-Limb Rehabilitation Robot Control Using GANs and Attention Mechanism. Machines, 9(12), Article 367. https://doi.org/10.33

To date, several alterations in the gait pattern can be treated through rehabilitative approaches and robot assisted therapy (RAT). Gait data and gait trajectories are essential in specific exoskeleton control strategies. Nevertheless, the scarcity o... Read More about Human Gait Data Augmentation and Trajectory Prediction for Lower-Limb Rehabilitation Robot Control Using GANs and Attention Mechanism.

Effect of velocity and acceleration in joint angle estimation for an EMG-Based upper-limb exoskeleton control (2021)
Journal Article
Tang, Z., Yu, H., Yang, H., Zhang, L., & Zhang, L. (2022). Effect of velocity and acceleration in joint angle estimation for an EMG-Based upper-limb exoskeleton control. Computers in Biology and Medicine, 141, Article 105156. https://doi.org/10.1016/j.com

Most studies on estimating user's joint angles to control upper-limb exoskeleton have focused on using surface electromyogram (sEMG) signals. However, the variations in limb velocity and acceleration can affect the sEMG data and decrease the angle es... Read More about Effect of velocity and acceleration in joint angle estimation for an EMG-Based upper-limb exoskeleton control.

A novel bipartite consensus tracking scheme for unknown nonlinear multi-agent systems: Theoretical analysis and applications (2021)
Journal Article
Zhao, H., Peng, L., Wu, P., & Yu, H. (2022). A novel bipartite consensus tracking scheme for unknown nonlinear multi-agent systems: Theoretical analysis and applications. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems a

This article proposes a novel distributed data-driven bipartite consensus tracking scheme for bipartite consensus tracking problems of multi-agent systems with bounded disturbances and coopetition networks. The proposed scheme only uses the input/out... Read More about A novel bipartite consensus tracking scheme for unknown nonlinear multi-agent systems: Theoretical analysis and applications.

Quantized model-free adaptive iterative learning bipartite consensus tracking for unknown nonlinear multi-agent systems (2021)
Journal Article
Zhao, H., Peng, L., & Yu, H. (2022). Quantized model-free adaptive iterative learning bipartite consensus tracking for unknown nonlinear multi-agent systems. Applied Mathematics and Computation, 412, Article 126582. https://doi.org/10.1016/j.amc.2021.1265

This paper considers the data quantization problem for a class of unknown nonaffine nonlinear discrete-time multi-agent systems (MASs) under repetitive operations to achieve bipartite consensus tracking. Here, a quantized distributed model-free adapt... Read More about Quantized model-free adaptive iterative learning bipartite consensus tracking for unknown nonlinear multi-agent systems.

Model-free adaptive consensus tracking control for unknown nonlinear multi-agent systems with sensor saturation (2021)
Journal Article
Zhao, H., Peng, L., & Yu, H. (2021). Model-free adaptive consensus tracking control for unknown nonlinear multi-agent systems with sensor saturation. International Journal of Robust and Nonlinear Control, 31(13), 6473-6491. https://doi.org/10.1002/rnc.563

This article proposes a distributed model-free adaptive consensus tracking control (DMFACTC) approach for a class of unknown heterogeneous nonlinear discrete-time multi-agent systems (MASs) with sensor saturation and measurement disturbance to perfor... Read More about Model-free adaptive consensus tracking control for unknown nonlinear multi-agent systems with sensor saturation.

Interoperability of the future factory: an overview of concepts and research challenges (2020)
Journal Article
Xu, L., Vrieze, P. D., Yu, H., Phalp, K., & Bai, Y. (2020). Interoperability of the future factory: an overview of concepts and research challenges. International Journal of Mechatronics and Manufacturing Systems, 13(1), 3-27. https://doi.org/10.1504/ijmm

Interoperability is a key factor in implementing a virtual factory. In European Union context interoperability is the ability of organisations to interact towards mutually beneficial goals, involving the sharing of information and knowledge between t... Read More about Interoperability of the future factory: an overview of concepts and research challenges.

An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling (2020)
Journal Article
Wu, P., Yang, Q., Chen, W., Mao, B., & Yu, H. (2020). An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling. Complexity, 2020, Article 3450180. https://doi.org/10.1155/2020/3450180

Due to the NP-hard nature, the permutation flowshop scheduling problem (PFSSP) is a fundamental issue for Industry 4.0, especially under higher productivity, efficiency, and self-managing systems. This paper proposes an improved genetic-shuffled frog... Read More about An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling.

A survey on underactuated robotic systems: Bio-inspiration, trajectory planning and control (2020)
Journal Article
Liu, P., Huda, M. N., Sun, L., & Yu, H. (2020). A survey on underactuated robotic systems: Bio-inspiration, trajectory planning and control. Mechatronics, 72, 102443. https://doi.org/10.1016/j.mechatronics.2020.102443

Underactuated robotic systems have become an important research topic aiming at significant improvement of the behavioural performance and energy efficiency. Adopting some bio-inspired ideas and properties, the self-organisation and main tasks of the... Read More about A survey on underactuated robotic systems: Bio-inspiration, trajectory planning and control.

Validity and Consistency of Concurrent Extraction of Gait Features Using Inertial Measurement Units and Motion Capture System (2020)
Journal Article
Anwary, A. R., Yu, H., Callaway, A., & Vassallo, M. (2021). Validity and Consistency of Concurrent Extraction of Gait Features Using Inertial Measurement Units and Motion Capture System. IEEE Sensors Journal, 21(2), 1625-1634. https://doi.org/10.1109/jsen

Conditions causing gait abnormalities are very common and their treatment requires the detailed assessment of gait. Currently such assessments are carried out in gait laboratories and require the use of complex and expensive equipment. To increase av... Read More about Validity and Consistency of Concurrent Extraction of Gait Features Using Inertial Measurement Units and Motion Capture System.

Data Driven Distributed Bipartite Consensus Tracking for Nonlinear Multiagent Systems via Iterative Learning Control (2020)
Journal Article
Zhao, H., Peng, L., & Yu, H. (2020). Data Driven Distributed Bipartite Consensus Tracking for Nonlinear Multiagent Systems via Iterative Learning Control. IEEE Access, 8, 144718-144729. https://doi.org/10.1109/access.2020.3014496

This article explores a data-driven distributed bipartite consensus tracking (DBCT) problem for discrete-time multi-agent systems (MASs) with coopetition networks under repeatable operations. To solve this problem, a time-varying linearization model... Read More about Data Driven Distributed Bipartite Consensus Tracking for Nonlinear Multiagent Systems via Iterative Learning Control.

Distributed Model-Free Bipartite Consensus Tracking for Unknown Heterogeneous Multi-Agent Systems with Switching Topology (2020)
Journal Article
Zhao, H., Peng, L., & Yu, H. (2020). Distributed Model-Free Bipartite Consensus Tracking for Unknown Heterogeneous Multi-Agent Systems with Switching Topology. Sensors, 20(15), Article 4164. https://doi.org/10.3390/s20154164

This paper proposes a distributed model-free adaptive bipartite consensus tracking (DMFABCT) scheme. The proposed scheme is independent of a precise mathematical model, but can achieve both bipartite time-invariant and time-varying trajectory trackin... Read More about Distributed Model-Free Bipartite Consensus Tracking for Unknown Heterogeneous Multi-Agent Systems with Switching Topology.

Analysis of a novel six-degree of freedom foldable parallel mechanism with optimized under-balance springs (2020)
Journal Article
Wang, C., Zhao, T., Yu, H., Li, E., Tian, X., & Ding, S. (2021). Analysis of a novel six-degree of freedom foldable parallel mechanism with optimized under-balance springs. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechani

The capacities of parallel mechanisms are limited by their height for the narrow space applications, such as the shipboard stability platforms, household simulators, aerospace mechanisms, etc. This paper proposes a novel foldable six-DOF parallel man... Read More about Analysis of a novel six-degree of freedom foldable parallel mechanism with optimized under-balance springs.

Gait quantification and visualization for digital healthcare (2020)
Journal Article
Anwary, A. R., Yu, H., & Vassallo, M. (2020). Gait quantification and visualization for digital healthcare. Health Policy and Technology, 9(2), 204-212. https://doi.org/10.1016/j.hlpt.2019.12.004

Gait abnormalities are common in clinical practice and there is a global imperative to improve technologies that facilitate their detection, evaluation, monitoring and management. Real time evaluation using digital technology supports the development... Read More about Gait quantification and visualization for digital healthcare.