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Wave-Net: A lightweight deep network for retinal vessel segmentation from fundus images (2022)
Journal Article
Liu, Y., Shen, J., Yang, L., Yu, H., & Bian, G. (2023). Wave-Net: A lightweight deep network for retinal vessel segmentation from fundus images. Computers in Biology and Medicine, 152, Article 106341. https://doi.org/10.1016/j.compbiomed.2022.106341

Accurate segmentation of retinal vessels from fundus images is fundamental for the diagnosis of numerous diseases of eye, and an automated vessel segmentation method can effectively help clinicians to make accurate diagnosis for the patients and prov... Read More about Wave-Net: A lightweight deep network for retinal vessel segmentation from fundus images.

DEF-Net: A Dual-Encoder Fusion Network for Fundus Retinal Vessel Segmentation (2022)
Journal Article
Li, J., Gao, G., Yang, L., Liu, Y., & Yu, H. (2022). DEF-Net: A Dual-Encoder Fusion Network for Fundus Retinal Vessel Segmentation. Electronics, 11(22), Article 3810. https://doi.org/10.3390/electronics11223810

The deterioration of numerous eye diseases is highly related to the fundus retinal structures, so the automatic retinal vessel segmentation serves as an essential stage for efficient detection of eye-related lesions in clinical practice. Segmentation... Read More about DEF-Net: A Dual-Encoder Fusion Network for Fundus Retinal Vessel Segmentation.

A Multi-robot Distributed Collaborative Region Coverage Search Algorithm Based on Glasius Bio-inspired Neural Network (2022)
Journal Article
Chen, B., Zhang, H., Zhang, F., Liu, Y., Tan, C., Yu, H., & Wang, Y. (2023). A Multi-robot Distributed Collaborative Region Coverage Search Algorithm Based on Glasius Bio-inspired Neural Network. IEEE Transactions on Cognitive and Developmental Systems, 15(3), 1449-1462. https://doi.org/10.1109/tcds.2022.3218718

There are many constraints for a multi-robot system to perform a region coverage search task in an unknown environment. To address this, we propose a novel multi-robot distributed collaborative region coverage search algorithm based on Glasius bio-in... Read More about A Multi-robot Distributed Collaborative Region Coverage Search Algorithm Based on Glasius Bio-inspired Neural Network.

A Multirobot Cooperative Area Coverage Search Algorithm Based on Bioinspired Neural Network in Unknown Environments (2022)
Journal Article
Chen, B., Zhang, W., Zhang, F., Liu, Y., & Yu, H. (2023). A Multirobot Cooperative Area Coverage Search Algorithm Based on Bioinspired Neural Network in Unknown Environments. IEEE Systems Journal, 17(2), 1995-2006. https://doi.org/10.1109/jsyst.2022.3198712

This article proposes a novel approach based on a bioinspired neural network (BIN) for multirobot area coverage search in unknown environments. We obtain the dynamic environment information in the search process of the multirobot by combining the BIN... Read More about A Multirobot Cooperative Area Coverage Search Algorithm Based on Bioinspired Neural Network in Unknown Environments.

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.2022.104087

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.org/10.1109/tnnls.2022.3174885

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://doi.org/10.4108/eetinis.v9i31.985

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://doi.org/10.1016/j.jvcir.2022.103454

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.

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.compbiomed.2021.105156

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/10.3390/machines9120367

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 and Control Engineering, 236(5), 1038-1048. https://doi.org/10.1177/09596518211060976

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.2021.126582

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.5630

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/ijmms.2020.108333

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.