Outputs (3144)

Geometric Visual Fusion Graph Neural Networks for Multi-Person Human-Object Interaction Recognition in Videos (2025)
Journal Article
Qiao, T., Li, R., Li, F. W. B., Kubotani, Y., Morishima, S., & Shum, H. P. H. (2025). Geometric Visual Fusion Graph Neural Networks for Multi-Person Human-Object Interaction Recognition in Videos. Expert Systems with Applications, 290, Article 128344. https://doi.org/10.1016/j.eswa.2025.128344

Human-Object Interaction (HOI) recognition in videos requires understanding both visual patterns and geometric relationships as they evolve over time. Visual and geometric features offer complementary strengths. Visual features capture appearance con... Read More about Geometric Visual Fusion Graph Neural Networks for Multi-Person Human-Object Interaction Recognition in Videos.

On the Design Fundamentals of Diffusion Models: A Survey (2025)
Journal Article
Chang, Z., Koulieris, G. A., Chang, H. J., & Shum, H. P. H. (in press). On the Design Fundamentals of Diffusion Models: A Survey. Pattern Recognition,

Talking Face Generation with Lip and Identity Priors (2025)
Journal Article
Wu, J., Li, F. W. B., Tam, G. K. L., Yang, B., Nan, F., & Pan, J. (2025). Talking Face Generation with Lip and Identity Priors. Computer Animation and Virtual Worlds, 36(3), Article e70026. https://doi.org/10.1002/cav.70026

Speech-driven talking face video generation has attracted growing interest in recent research. While person-specific approaches yield high-fidelity results, they require extensive training data from each individual speaker. In contrast, general-purpo... Read More about Talking Face Generation with Lip and Identity Priors.

Inference-Time Decomposition of Activations (ITDA): A Scalable Approach to Interpreting Large Language Models (2025)
Presentation / Conference Contribution
Leask, P., & Al Moubayed, N. (2025, July). Inference-Time Decomposition of Activations (ITDA): A Scalable Approach to Interpreting Large Language Models. Presented at International Conference on Machine Learning (ICML 2025), Vancouver, Canada

Sparse Autoencoders (SAEs) are a popular method for decomposing Large Language Model (LLM) activations into interpretable latents, however they have a substantial training cost and SAEs learned on different models are not directly comparable. Motivat... Read More about Inference-Time Decomposition of Activations (ITDA): A Scalable Approach to Interpreting Large Language Models.

CLN: A multi-task deep neural network for chest X-ray image localisation and classification (2025)
Journal Article
Okolo, G. I., Katsigiannis, S., & Ramzan, N. (2025). CLN: A multi-task deep neural network for chest X-ray image localisation and classification. Expert Systems with Applications, 288, Article 128162. https://doi.org/10.1016/j.eswa.2025.128162

Chest X-ray (CXR) imaging is a widely used and cost-effective medical imaging technique for detecting various pathologies. However, accurate interpretation of CXR images is a challenging and time-consuming task that requires expert radiologists. Alth... Read More about CLN: A multi-task deep neural network for chest X-ray image localisation and classification.

Service-the-Longest-Queue Among d Choices Policy for Quantum Entanglement Switching (2025)
Presentation / Conference Contribution
Yau, G. X., Vasantam, T., & Vardoyan, G. (2025, March). Service-the-Longest-Queue Among d Choices Policy for Quantum Entanglement Switching. Presented at QCNC2025: International Conference on Quantum Communications, Networking, and Computing, Nara, Japan

An Entanglement Generation Switch (EGS) is a quantum network hub that provides entangled states to a set of connected nodes by enabling them to share a limited number of hub resources. As entanglement requests arrive, they join dedicated queues corre... Read More about Service-the-Longest-Queue Among d Choices Policy for Quantum Entanglement Switching.

weDecide: Clinical Tool for Shared Decision-Making for Treatment of Menopause Symptoms (2025)
Presentation / Conference Contribution
Bencomo, N., Horrocks, J., Walton, D., & Samin, H. (2025, June). weDecide: Clinical Tool for Shared Decision-Making for Treatment of Menopause Symptoms. Presented at BMS Annual Scientific Conference 2025, Chesford Grange, Kenilworth, UK

This work introduces weDecide, an AI/ML-based clinical tool designed to support personalised and shared decision-making (PSDM) for menopause treatment. The tool combines explainable machine learning models with multi-criteria decision-making methods... Read More about weDecide: Clinical Tool for Shared Decision-Making for Treatment of Menopause Symptoms.

SPECTRA: A Markovian Framework for Managing NFR Tradeoffs in Systems with Mixed Observability (2025)
Journal Article
Ignatius, H. T. N., Bahsoon, R., Bencomo, N., & Samin, H. (online). SPECTRA: A Markovian Framework for Managing NFR Tradeoffs in Systems with Mixed Observability. ACM Transactions on Autonomous and Adaptive Systems, https://doi.org/10.1145/3735643

Non-Functional Requirements (NFRs) play a critical role in driving self-adaptation in software systems. In Self-Adaptive Systems (SAS), satisfying multiple NFRs simultaneously introduces significant complexity, as these requirements often conflict-im... Read More about SPECTRA: A Markovian Framework for Managing NFR Tradeoffs in Systems with Mixed Observability.

Acyclic, star and injective colouring: A complexity picture for H-free graphs (2025)
Journal Article
Bok, J., Jedličková, N., Martin, B., Ochem, P., Paulusma, D., & Smith, S. (2025). Acyclic, star and injective colouring: A complexity picture for H-free graphs. Journal of Computer and System Sciences, 154, Article 103662. https://doi.org/10.1016/j.jcss.2025.103662

A (proper) colouring is acyclic, star, or injective if any two colour classes induce a forest, star forest or disjoint union of vertices and edges, respectively. The corresponding decision problems are Acyclic Colouring, Star Colouring and Injective... Read More about Acyclic, star and injective colouring: A complexity picture for H-free graphs.

High-Throughput Wireless Uplink Transmissions Using Self-Powered Hybrid RISs (2025)
Presentation / Conference Contribution
Yuan, M., Chen, L., Huang, G., Tu, W., Huang, Z., & Alshaali, M. (2025, March). High-Throughput Wireless Uplink Transmissions Using Self-Powered Hybrid RISs. Presented at 2025 IEEE Wireless Communications and Networking Conference (WCNC), Milan, Italy

This article investigates the uplink of a reconfigurable intelligent surface (RIS)-assisted wireless communication system. In this uplink, the RIS is powered by the energy harvested from ambient energy sources, and assists multiple users in uploading... Read More about High-Throughput Wireless Uplink Transmissions Using Self-Powered Hybrid RISs.