Outputs (200)

Effects of Prior Experience, Gender, and Age on Trust in a Banking Chatbot with(out) Breakdown and Repair (2023)
Presentation / Conference Contribution
Lai-Chong Law, E., van As, N., & Følstad, A. (2023, August). Effects of Prior Experience, Gender, and Age on Trust in a Banking Chatbot with(out) Breakdown and Repair. Presented at INTERACT 2023: 19th International Conference of Technical Committee 13 (Human- Computer Interaction) of IFIP (International Federation for Information Processing), York, UK

Trust is an attitudinal construct that can be sensitive to prior experience, gender, and age. In our study, we explored how trust in a banking chatbot might be shaped by these user characteristics. Statistical analysis of 251 participants, who intera... Read More about Effects of Prior Experience, Gender, and Age on Trust in a Banking Chatbot with(out) Breakdown and Repair.

Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function (2023)
Journal Article
Chambers, P., Watson, M., Bridgewater, J., Forster, M. D., Roylance, R., Burgoyne, R., Masento, S., Steventon, L., Harmsworth King, J., Duncan, N., & al Moubayed, N. (2023). Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function. Cancer Medicine, 12(17), 17856-17865. https://doi.org/10.1002/cam4.6418

Background
In those receiving chemotherapy, renal and hepatic dysfunction can increase the risk of toxicity and should therefore be monitored. We aimed to develop a machine learning model to identify those patients that need closer monitoring, enabl... Read More about Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function.

ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction (2023)
Presentation / Conference Contribution
Yu, Z., Haung, S., Fang, C., Breckon, T., & Wang, J. (2023, June). ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction. Presented at IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023, Vancouver, BC

Reconstructing two hands from monocular RGB images is challenging due to frequent occlusion and mutual confusion. Existing methods mainly learn an entangled representation to encode two interacting hands, which are incredibly fragile to impaired inte... Read More about ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction.

Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation (2023)
Presentation / Conference Contribution
Li, L., Shum, H. P., & Breckon, T. P. (2023, June). Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation. Presented at 2023 IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), Vancouver, BC

Whilst the availability of 3D LiDAR point cloud data has significantly grown in recent years, annotation remains expensive and time-consuming, leading to a demand for semisupervised semantic segmentation methods with application domains such as auton... Read More about Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation.

WDFSR: Normalizing Flow based on Wavelet-Domain for Super-Resolution (2023)
Journal Article
Song, C., Li, S., Li, F. W. B., & Yang, B. (in press). WDFSR: Normalizing Flow based on Wavelet-Domain for Super-Resolution. Computational Visual Media,

We propose a Normalizing flow based on the wavelet framework for super-resolution called WDFSR. It learns the conditional distribution mapping between low-resolution images in the RGB domain and high-resolution images in the wavelet domain to generat... Read More about WDFSR: Normalizing Flow based on Wavelet-Domain for Super-Resolution.

Predicting acute clinical deterioration with interpretable machine learning to support emergency care decision making (2023)
Journal Article
Boulitsakis Logothetis, S., Green, D., Holland, M., & Al Moubayed, N. (2023). Predicting acute clinical deterioration with interpretable machine learning to support emergency care decision making. Scientific Reports, 13(1), Article 13563. https://doi.org/10.1038/s41598-023-40661-0

The emergency department (ED) is a fast-paced environment responsible for large volumes of patients with varied disease acuity. Operational pressures on EDs are increasing, which creates the imperative to efficiently identify patients at imminent ris... Read More about Predicting acute clinical deterioration with interpretable machine learning to support emergency care decision making.

Sliding into the Future: Investigating Sliding Windows in Temporal Graphs (2023)
Presentation / Conference Contribution
Klobas, N., Mertzios, G. B., & Spirakis, P. G. (2023, August). Sliding into the Future: Investigating Sliding Windows in Temporal Graphs. Presented at 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023), Bordeaux, France

Dichotomies for Maximum Matching Cut: H-Freeness, Bounded Diameter, Bounded Radius (2023)
Presentation / Conference Contribution
Lucke, F., Paulusma, D., & Ries, B. (2023, August). Dichotomies for Maximum Matching Cut: H-Freeness, Bounded Diameter, Bounded Radius. Presented at 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023), Bordeaux, France

The (Perfect) Matching Cut problem is to decide if a graph G has a (perfect) matching cut, i.e., a (perfect) matching that is also an edge cut of G. Both Matching Cut and Perfect Matching Cut are known to be NP-complete, leading to many complexity re... Read More about Dichotomies for Maximum Matching Cut: H-Freeness, Bounded Diameter, Bounded Radius.

Complexity Framework for Forbidden Subgraphs III: When Problems are Tractable on Subcubic Graphs (2023)
Presentation / Conference Contribution
Johnson, M., Martin, B., Pandey, S., Paulusma, D., Smith, S., & Van Leeuwen, E. J. (2023, August). Complexity Framework for Forbidden Subgraphs III: When Problems are Tractable on Subcubic Graphs. Presented at 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023), Bordeaux, France

For any finite set H = {H1,. .. , Hp} of graphs, a graph is H-subgraph-free if it does not contain any of H1,. .. , Hp as a subgraph. In recent work, meta-classifications have been studied: these show that if graph problems satisfy certain prescribed... Read More about Complexity Framework for Forbidden Subgraphs III: When Problems are Tractable on Subcubic Graphs.

Complex online harms and the smart home: A scoping review (2023)
Journal Article
Olabode, S., Owens, R., Zhang, V. N., Copilah-Ali, J., Kolomeets, M., Wu, H., …Chambers, D. (2023). Complex online harms and the smart home: A scoping review. Future Generation Computer Systems, 149, 664-678. https://doi.org/10.1016/j.future.2023.08.019

Background:
Technological advances in the smart home have created new opportunities for supporting digital citizens’ well-being and facilitating their empowerment but have enabled new types of complex online harms to develop. Recent statistics have... Read More about Complex online harms and the smart home: A scoping review.