Skip to main content

Research Repository

Advanced Search

Outputs (3164)

Maximizing Matching Cuts (2024)
Book Chapter
Le, V. B., Lucke, F., Paulusma, D., & Ries, B. (2024). Maximizing Matching Cuts. In P. M. Pardalos, & O. A. Prokopyev (Eds.), Encyclopedia of Optimization (1-10). Springer Nature. https://doi.org/10.1007/978-3-030-54621-2_898-1

Graph cut problems belong to a well-studied class of classical graph problems related to network connectivity, which is a central concept within theoretical computer science.

SIRT2 Inhibition by AGK2 Promotes Perinuclear Cytoskeletal Organisation and Reduces Invasiveness of MDA-MB-231 Triple-Negative Breast Cancer Cells in Confined In Vitro Models (2024)
Journal Article
Jessop, E., Young, N., Garcia-Del-Valle, B., Crusher, J. T., Obara, B., & Karakesisoglou, I. (2024). SIRT2 Inhibition by AGK2 Promotes Perinuclear Cytoskeletal Organisation and Reduces Invasiveness of MDA-MB-231 Triple-Negative Breast Cancer Cells in Confined In Vitro Models. Cells, 13(23), Article 2023. https://doi.org/10.3390/cells13232023

Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer subtype characterised by the absence of targetable hormone receptors and increased metastatic rates. As nuclear softening strongly contributes to TNBC’s enhanced metastatic cap... Read More about SIRT2 Inhibition by AGK2 Promotes Perinuclear Cytoskeletal Organisation and Reduces Invasiveness of MDA-MB-231 Triple-Negative Breast Cancer Cells in Confined In Vitro Models.

Neural-code PIFu: High-fidelity Single Image 3D Human Reconstruction via Neural Code Integration (2024)
Presentation / Conference Contribution
Liu, R., Remagnino, P., & Shum, H. P. (2024, December). Neural-code PIFu: High-fidelity Single Image 3D Human Reconstruction via Neural Code Integration. Presented at 2024 International Conference on Pattern Recognition, Kolkata, India

We introduce neural-code PIFu, a novel implicit function for 3D human reconstruction, leveraging neural codebooks, our approach learns recurrent patterns in the feature space and reuses them to improve current features. Many existing methods predict... Read More about Neural-code PIFu: High-fidelity Single Image 3D Human Reconstruction via Neural Code Integration.

Intelligent edge–fog interplay for healthcare informatics: A blockchain perspective (2024)
Journal Article
Rathore, N., Gupta, R., Thakkar, N., Gohil, K., Tanwar, S., Aujla, G. S., Alqahtani, F., & Tolba, A. (2025). Intelligent edge–fog interplay for healthcare informatics: A blockchain perspective. Ad Hoc Networks, 169, Article 103727. https://doi.org/10.1016/j.adhoc.2024.103727

This paper explores artificial intelligence (AI) and edge–fog interplay to strengthen healthcare informatics (HCI), while also considering the blockchain perspective for securing HCI to transform cloud-based HCI to edge–fog-based HCI to serve real-ti... Read More about Intelligent edge–fog interplay for healthcare informatics: A blockchain perspective.

Performance of machine learning versus the national early warning score for predicting patient deterioration risk: a single-site study of emergency admissions (2024)
Journal Article
Watson, M., Boulitsakis Logothetis, S., Green, D., Holland, M., Chambers, P., & Al Moubayed, N. (2024). Performance of machine learning versus the national early warning score for predicting patient deterioration risk: a single-site study of emergency admissions. BMJ Health & Care Informatics, 31(1), Article e101088. https://doi.org/10.1136/bmjhci-2024-101088

Objectives: Increasing operational pressures on emergency departments (ED) make it imperative to quickly and accurately identify patients requiring urgent clinical intervention. The widespread adoption of electronic health records (EHR) makes rich fe... Read More about Performance of machine learning versus the national early warning score for predicting patient deterioration risk: a single-site study of emergency admissions.

From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos (2024)
Presentation / Conference Contribution
Qiao, T., Li, R., Li, F. W. B., & Shum, H. P. H. (2024, December). From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos. Presented at ICPR 2024: International Conference on Pattern Recognition, Kolkata, India

Video-based Human-Object Interaction (HOI) recognition explores the intricate dynamics between humans and objects, which are essential for a comprehensive understanding of human behavior and intentions. While previous work has made significant stride... Read More about From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos.

Complexity framework for forbidden subgraphs II: Edge subdivision and the "H"-graphs (2024)
Presentation / Conference Contribution
Lozin, V. V., Martin, B., Pandey, S., Paulusma, D., Siggers, M., Smith, S., & van Leeuwen, E. J. (2024, December). Complexity framework for forbidden subgraphs II: Edge subdivision and the "H"-graphs. Presented at ISAAC, ISAAC 2024

For a fixed set H of graphs, a graph G is H-subgraph-free if G does not contain any H ∈ H as a (not necessarily induced) subgraph. A recent framework gives a complete classification on H-subgraph-free graphs (for finite sets H) for problems that are... Read More about Complexity framework for forbidden subgraphs II: Edge subdivision and the "H"-graphs.

SK_DU Team: Cross-Encoder based Evidence Retrieval and Question Generation with Improved Prompt for the AVeriTeC Shared Task (2024)
Presentation / Conference Contribution
Malviya, S., & Katsigiannis, S. (2024, November). SK_DU Team: Cross-Encoder based Evidence Retrieval and Question Generation with Improved Prompt for the AVeriTeC Shared Task. Presented at 7th Fact Extraction and VERification Workshop (FEVER), Miami, Florida, USA

As part of the AVeriTeC shared task, we developed a pipelined system comprising robust and finely tuned models. Our system integrates advanced techniques for evidence retrieval and question generation, leveraging cross-encoders and large language mod... Read More about SK_DU Team: Cross-Encoder based Evidence Retrieval and Question Generation with Improved Prompt for the AVeriTeC Shared Task.

6DGS: 6D Pose Estimation from a Single Image and a 3D Gaussian Splatting Model (2024)
Presentation / Conference Contribution
Matteo, B., Tsesmelis, T., James, S., Poiesi, F., & Del Bue, A. (2024, September). 6DGS: 6D Pose Estimation from a Single Image and a 3D Gaussian Splatting Model. Presented at Computer Vision – ECCV 2024 18th European Conference, Milan, Italy

We propose 6DGS to estimate the camera pose of a target RGB image given a 3D Gaussian Splatting (3DGS) model representing the scene. 6DGS avoids the iterative process typical of analysis-by-synthesis methods (e. g.iNeRF) that also require an initiali... Read More about 6DGS: 6D Pose Estimation from a Single Image and a 3D Gaussian Splatting Model.