All Outputs (10)

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.

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.

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.

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.