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Outputs (3144)

Large-Scale Multi-Character Interaction Synthesis (2025)
Presentation / Conference Contribution
Chang, Z., Wang, H., Koulieris, G. A., & Shum, H. P. (2025, August). Large-Scale Multi-Character Interaction Synthesis. Presented at ACM SIGGRAPH 2025, Vancouver, Canada

T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles (2025)
Journal Article
Pan, H., Zahmatkesh, M., Rekabi-Bana, F., Arvin, F., & Hu, J. (online). T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles. IEEE Transactions on Intelligent Transportation Systems, https://doi.org/10.1109/TITS.2025.3557783

This paper introduces a time-optimal swarm tra-jectory planner for cooperative unmanned aerial vehicle (UAV) systems, designed to generate collision-free trajectories for flocking control in cluttered environments. To achieve this goal, model predict... Read More about T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles.

Realizing temporal transportation trees (2025)
Presentation / Conference Contribution
Mertzios, G., Molter, H., Morawietz, N., & Spirakis, P. (2025, June). Realizing temporal transportation trees. Presented at 51st International Workshop on Graph-Theoretic Concepts in Computer Science (WG 2025), Otzenhausen, Germany

SEM-Net: Efficient Pixel Modelling for Image Inpainting with Spatially Enhanced SSM (2025)
Presentation / Conference Contribution
Chen, S., Zhang, H., Atapour-Abarghouei, A., & Shum, H. P. H. (2025, February). SEM-Net: Efficient Pixel Modelling for Image Inpainting with Spatially Enhanced SSM. Presented at 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Tucson, Arizona

Image inpainting aims to repair a partially damaged image based on the information from known regions of the images. Achieving semantically plausible inpainting results is particularly challenging because it requires the reconstructed regions to exhi... Read More about SEM-Net: Efficient Pixel Modelling for Image Inpainting with Spatially Enhanced SSM.

Human Intracranial EEG Biometric Identification (2025)
Presentation / Conference Contribution
Belay, B., & Katsigiannis, S. (2025, July). Human Intracranial EEG Biometric Identification. Presented at International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC), Copenhagen, Denmark

FMDConv: Fast multi-attention dynamic convolution via speed-accuracy trade-off (2025)
Journal Article
Zhang, T., Wan, F., Duan, H., Tong, K. W., Deng, J., & Long, Y. (2025). FMDConv: Fast multi-attention dynamic convolution via speed-accuracy trade-off. Knowledge-Based Systems, 317, Article 113393. https://doi.org/10.1016/j.knosys.2025.113393

Spatial convolution is fundamental in constructing deep Convolutional Neural Networks (CNNs) for visual recognition. While dynamic convolution enhances model accuracy by adaptively combining static kernels, it incurs significant computational overhe... Read More about FMDConv: Fast multi-attention dynamic convolution via speed-accuracy trade-off.

Towards empathic medical conversation in Narrative Medicine: A visualization approach based on intelligence augmentation (2025)
Journal Article
Ma, H., Law, E. L.-C., Sun, X., Yang, W., He, X., Lawson, G., Zheng, H., Wang, Q., Li, Q., & Yuan, X. (2025). Towards empathic medical conversation in Narrative Medicine: A visualization approach based on intelligence augmentation. International Journal of Human-Computer Studies, 199, Article 103506. https://doi.org/10.1016/j.ijhcs.2025.103506

Empathic medical conversation is central to patient-centered care within Narrative Medicine. However, difficulties, such as physicians’ limited empathic capabilities and lack of time, impede the practice. Research on real-time, on-site empathic medic... Read More about Towards empathic medical conversation in Narrative Medicine: A visualization approach based on intelligence augmentation.

Model‐Driven Engineering for Digital Twins: Opportunities and Challenges (2025)
Journal Article
Michael, J., Cleophas, L., Zschaler, S., Clark, T., Combemale, B., Godfrey, T., Khelladi, D. E., Kulkarni, V., Lehner, D., Rumpe, B., Wimmer, M., Wortmann, A., Ali, S., Barn, B., Barosan, I., Bencomo, N., Bordeleau, F., Grossmann, G., Karsai, G., Kopp, O., …Vangheluwe, H. (online). Model‐Driven Engineering for Digital Twins: Opportunities and Challenges. Systems Engineering, https://doi.org/10.1002/sys.21815

Digital twins are increasingly used across a wide range of industries. Modeling is a key to digital twin development—both when considering the models which a digital twin maintains of its real‐world complement (“models in digital twin”) and when cons... Read More about Model‐Driven Engineering for Digital Twins: Opportunities and Challenges.