All Outputs (123)

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.

An Improved Point-to-Feature Recognition Algorithm for 3D Vision Detection (2022)
Presentation / Conference Contribution
Li, J., Guo, Q., Gao, G., Tang, S., Min, G., Li, C., & Yu, H. (2022). An Improved Point-to-Feature Recognition Algorithm for 3D Vision Detection. In Intelligent Robotics and Applications. ICIRA 2022 (197-209). https://doi.org/10.1007/978-3-031-13822-5_1

Vision-detection-based grasping is one of the research hotspots in the field of automated production. As the grasping scenes become more and more diversified, 3D images are increasingly chosen as the input images for object recognition in complex rec... Read More about An Improved Point-to-Feature Recognition Algorithm for 3D Vision Detection.

Improved Cascade Active Disturbance Rejection Control for Functional Electrical Stimulation Based Wrist Tremor Suppression System Considering the Effect of Output Noise (2022)
Presentation / Conference Contribution
Tao, C., Zhang, Z., Huo, B., Liu, Y., Li, J., & Yu, H. (2022). Improved Cascade Active Disturbance Rejection Control for Functional Electrical Stimulation Based Wrist Tremor Suppression System Considering the Effect of Output Noise. In Intelligent Rob

The wrist tremor suppression system designed based on functional electrical stimulation technology has been welcomed by the majority of tremor patients as a non-invasive rehabilitation therapy. Due to the complex physiological structure characteristi... Read More about Improved Cascade Active Disturbance Rejection Control for Functional Electrical Stimulation Based Wrist Tremor Suppression System Considering the Effect of Output Noise.

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.

A case study: effect of wrist sensor displacement on HAR performance using LSTM and attention mechanism (2022)
Presentation / Conference Contribution
Wang, X., Wang, Y., Lu, C., Yu, H., He, H., & Li, Z. (2022). A case study: effect of wrist sensor displacement on HAR performance using LSTM and attention mechanism. In 2021 International Conference on Advanced Mechatronic Systems (ICAMechS) (103-108). h

Loose wearing or self-placement usually causes sensor displacement, which can deteriorate the performance of classifiers in real use. As a case study, this paper focuses on investigating the effect of wrist-worn sensor displacement on human activity... Read More about A case study: effect of wrist sensor displacement on HAR performance using LSTM 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.

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.

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.

Processing and characterisation of water hyacinth cellulose nanofibres-based aluminium-ion battery separators (2021)
Presentation / Conference Contribution
Beg, M., Sun, D., Popescu, C., Alcock, K. M., Onyianta, A. J., O'Rourke, D., …Yu, H. (2021). Processing and characterisation of water hyacinth cellulose nanofibres-based aluminium-ion battery separators. In 2021 26th International Conference on Automat

Water hyacinth is an invasive plant that can be converted to high value cellulose nanofibers. This study presents battery separators prepared from water hyacinth cellulose nanofibres (WHCNF) via a freeze-thawing crosslinking method, using polyethylen... Read More about Processing and characterisation of water hyacinth cellulose nanofibres-based aluminium-ion battery separators.

Observer-Based Adaptive Sliding Mode Control for Soft Actuators with Input Constraints (2021)
Presentation / Conference Contribution
Cao, G., Shi, H., Xia, D., Zheng, Y., Liu, Y., & Yu, H. (2022). Observer-Based Adaptive Sliding Mode Control for Soft Actuators with Input Constraints. In Proceedings of 2021 Chinese Intelligent Automation Conference (524-533). https://doi.org/10.1007/97

Fabricated by superelastic materials, soft actuators are an emerging field to provide a solution of safe interaction with complicated, unstructured and frequently brittle work environments, while they also bear challenges in fragility and controlling... Read More about Observer-Based Adaptive Sliding Mode Control for Soft Actuators with Input Constraints.

Electromyographic Signal Based Dynamic Hand Gesture Recognition Using Transfer Learning (2021)
Presentation / Conference Contribution
Song, S., Yang, L., Huo, B., Wu, M., Liu, Y., & Yu, H. (2022). Electromyographic Signal Based Dynamic Hand Gesture Recognition Using Transfer Learning. In Proceedings of 2021 Chinese Intelligent Automation Conference (389-397). https://doi.org/10.1007/97

Recent years, the research of gesture recognition based on surface EMG signal has become an active topic. The conventional methods mainly focus on feature engineering, but the sEMG signal is non-stationary temporally, which makes proper feature desig... Read More about Electromyographic Signal Based Dynamic Hand Gesture Recognition Using Transfer Learning.

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.