Outputs (187)

Feature fine-tuning and attribute representation transformation for zero-shot learning (2023)
Journal Article
Pang, S., He, X., Hao, W., & Long, Y. (2023). Feature fine-tuning and attribute representation transformation for zero-shot learning. Computer Vision and Image Understanding, 236, Article 103811. https://doi.org/10.1016/j.cviu.2023.103811

Zero-Shot Learning (ZSL) aims to generalize a pretrained classification model to unseen classes with the help of auxiliary semantic information. Recent generative methods are based on the paradigm of synthesizing unseen visual data from class attribu... Read More about Feature fine-tuning and attribute representation transformation for zero-shot learning.

Evaluation of a hybrid AI-human recommender for CS1 instructors in a real educational scenario (2023)
Presentation / Conference Contribution
Dwan Pereira, F., Oliveira, E., Rodrigues, L., Cabral, L., Oliveira, D., Carvalho, L., Gasevic, D., Cristea, A., Dermeval, D., & Ferreira Mello, R. (2023, September). Evaluation of a hybrid AI-human recommender for CS1 instructors in a real educational scenario. Presented at Eighteenth European Conference on Technology Enhanced Learning: ECTEL 2023, Aveiro, Portugal

Automatic code graders, also called Programming Online Judges (OJ), can support students and instructors in introduction to programming courses (CS1). Using OJs in CS1, instructors select problems to compose assignment lists, whereas students submit... Read More about Evaluation of a hybrid AI-human recommender for CS1 instructors in a real educational scenario.

Exploring the Potential of Immersive Virtual Environments for Learning American Sign Language (2023)
Presentation / Conference Contribution
Wang, J., Ivrissimtzis, I., Li, Z., Zhou, Y., & Shi, L. (2023, September). Exploring the Potential of Immersive Virtual Environments for Learning American Sign Language. Presented at ECTEL 2023: Eighteenth European Conference on Technology Enhanced Learning, Aveiro, Portugal

Sign languages enable effective communication between deaf and hearing people. Despite years of extensive pedagogical research, learning sign language online comes with a number of difficulties that might be frustrating for some students. Indeed, mos... Read More about Exploring the Potential of Immersive Virtual Environments for Learning American Sign Language.

To download or not to download the Covid-19 Track and Trace App? What is more influential in users’ minds? (2023)
Journal Article
Sutcliffe, A., Bencomo, N., Darby, A., Paucar, L. H., & Sawyer, P. (2023). To download or not to download the Covid-19 Track and Trace App? What is more influential in users’ minds?. International Journal of Human-Computer Studies, 180, Article 103140. https://doi.org/10.1016/j.ijhcs.2023.103140

Objectives
to investigate the role of values in technology acceptance in general and in the context of the UK Covid Track and Trace App.

Methods
A survey and interview study was conducted to elicit users’ perceptions of values in general, values... Read More about To download or not to download the Covid-19 Track and Trace App? What is more influential in users’ minds?.

Developing and Evaluating a Novel Gamified Virtual Learning Environment for ASL (2023)
Presentation / Conference Contribution
Wang, J., Ivrissimtzis, I., Li, Z., Zhou, Y., & Shi, L. (2023, August). Developing and Evaluating a Novel Gamified Virtual Learning Environment for ASL. Presented at INTERACT 2023: IFIP Conference on Human-Computer Interaction, York

The use of sign language is a highly effective way of communicating with individuals who experience hearing loss. Despite extensive research, many learners find traditional methods of learning sign language, such as web-based question-answer methods,... Read More about Developing and Evaluating a Novel Gamified Virtual Learning Environment for ASL.

Empirical Grounding for the Interpretations of Natural User Interface: A Case Study on Smartpen (2023)
Presentation / Conference Contribution
Alabdulwahab, B., & Lai-Chong Law, E. (2023, August). Empirical Grounding for the Interpretations of Natural User Interface: A Case Study on Smartpen. Presented at INTERACT 2023: 19th International Conference of Technical Committee 13 (Human- Computer Interaction) of IFIP (International Federation for Information Processing), York, UK

The emergence of Natural User Interface (NUI) approximately two decades ago promised to support intuitive and multimodal interactions by leveraging human sensorimotor skills such as touching, speaking, and gazing. Despite the development and introduc... Read More about Empirical Grounding for the Interpretations of Natural User Interface: A Case Study on Smartpen.

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., …al Moubayed, N. (2023). Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function. Cancer Medicine, 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.

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). Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/CVPR52729.2023.00903

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.

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). ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/CVPR52729.2023.01245

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.