Outputs (492)

An Input Sampling Scheme to Radar Echo Extrapolation For RNN-Based Models (2022)
Presentation / Conference Contribution
Wang, Y., Yang, Z., Liu, Q., & Liu, X. (2022, September). An Input Sampling Scheme to Radar Echo Extrapolation For RNN-Based Models. Presented at 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), Falerna, Italy

Short-term heavy rainfall can have a significant impact on people's production, life and travel. Numerical Weather Prediction (NWP) is complex. It can predict weather conditions for the next week or even two weeks, but cannot predict the weather in t... Read More about An Input Sampling Scheme to Radar Echo Extrapolation For RNN-Based Models.

CFNet: An Eigenvalue Preserved Approach to Multiscale Building Segmentation in High-Resolution Remote Sensing Images (2023)
Journal Article
Liu, Q., Li, Y., Bilal, M., Liu, X., Zhang, Y., Wang, H., & Xu, X. (2023). CFNet: An Eigenvalue Preserved Approach to Multiscale Building Segmentation in High-Resolution Remote Sensing Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 2481-2491. https://doi.org/10.1109/jstars.2023.3244336

In recent years, AI and Deep Learning (DL) methods have been widely used for object classification, recognition, and segmentation of high-resolution multispectral remote sensing images. These DL-based solutions perform better compare to traditional s... Read More about CFNet: An Eigenvalue Preserved Approach to Multiscale Building Segmentation in High-Resolution Remote Sensing Images.

A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms (2023)
Presentation / Conference Contribution
Montague, K., Hart, E., Paechter, B., & Nitschke, G. (2023, April). A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms. Presented at EVOStar 2023, Brno, Czechia

Designing controllers for a swarm of robots such that collabo-rative behaviour emerges at the swarm level is known to be challenging. Evolutionary approaches have proved promising, with attention turning more recently to evolving repertoires of dive... Read More about A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms.

DIGNEA: A tool to generate diverse and discriminatory instance suites for optimisation domains (2023)
Journal Article
Marrero, A., Segredo, E., León, C., & Hart, E. (2023). DIGNEA: A tool to generate diverse and discriminatory instance suites for optimisation domains. SoftwareX, 22, Article 101355. https://doi.org/10.1016/j.softx.2023.101355

To advance research in the development of optimisation algorithms, it is crucial to have access to large test-beds of diverse and discriminatory instances from a domain that can highlight strengths and weaknesses of different algorithms. The DIGNEA t... Read More about DIGNEA: A tool to generate diverse and discriminatory instance suites for optimisation domains.

Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP (2023)
Presentation / Conference Contribution
Datta, S., Ganguly, D., Mothe, J., & Ullah, M. Z. (2023, April). Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP. Presented at 45th European Conference on Information Retrieval (ECIR), Dublin, Ireland

In information retrieval, query performance prediction aims to predict whether a search engine is likely to succeed in retrieving potentially relevant documents to a user's query. This problem is usually cast into a regression problem where a machine... Read More about Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP.

DanceGraph: A Complementary Architecture for Synchronous Dancing Online (2023)
Presentation / Conference Contribution
Sinclair, D., Ademola, A. V., Koniaris, B., & Mitchell, K. (2023, May). DanceGraph: A Complementary Architecture for Synchronous Dancing Online. Paper presented at 36th International Computer Animation & Social Agents (CASA) 2023, Limassol, Cyprus

DanceGraph is an architecture for synchronized online dancing overcoming the latency of net-worked body pose sharing. We break down this challenge by developing a real-time bandwidth-efficient architecture to minimize lag and reduce the timeframe of... Read More about DanceGraph: A Complementary Architecture for Synchronous Dancing Online.

Towards Improving Accessibility of Web Auditing with Google Lighthouse (2023)
Presentation / Conference Contribution
McGill, T., Bamgboye, O., Liu, X., & Kalutharage, C. S. (2023, June). Towards Improving Accessibility of Web Auditing with Google Lighthouse. Presented at The 47th IEEE Annual Conference on Computers, Software, and Applications (COMPSAC), Turin, Italy

Google Lighthouse is a tool made by Google for auditing web pages performance, accessibility, SEO, and best practices with the intention of improving the quality of the websites. This allows software developers to understand areas of improvement with... Read More about Towards Improving Accessibility of Web Auditing with Google Lighthouse.

Editorial: Games May Host the First Rightful AI Citizens (2023)
Journal Article
Mitchell, K. (2023). Editorial: Games May Host the First Rightful AI Citizens. Games: Research and Practice, 1(2), 1-7. https://doi.org/10.1145/3606834

GAMES creatively take place in imaginative worlds informed by, but often not limited by, real-world challenges, and this advantageously provides an accelerated environment for innovation, where concepts and ideas can be explored unencumbered by physi... Read More about Editorial: Games May Host the First Rightful AI Citizens.

A cloud-based Bi-directional LSTM approach to grid-connected solar PV energy forecasting for multi-energy systems (2023)
Journal Article
Liu, Q., Darteh, O. F., Bilal, M., Huang, X., Attique, M., Liu, X., & Acakpovi, A. (2023). A cloud-based Bi-directional LSTM approach to grid-connected solar PV energy forecasting for multi-energy systems. Sustainable Computing, 40, Article 100892. https://doi.org/10.1016/j.suscom.2023.100892

The drive for smarter, greener, and more livable cities has led to research towards more effective solar energy forecasting techniques and their integration into traditional power systems. However, the availability of real-time data, data storage, an... Read More about A cloud-based Bi-directional LSTM approach to grid-connected solar PV energy forecasting for multi-energy systems.

Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization (2024)
Journal Article
Zeng, L., Liu, Q., Shen, S., & Liu, X. (2024). Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization. Tsinghua Science and Technology, 29(3), 806 - 817. https://doi.org/10.26599/TST.2023.9010058

Edge computing nodes undertake more and more tasks as business density grows. How to efficiently allocate large-scale and dynamic workloads to edge computing resources has become a critical challenge. An edge task scheduling approach based on an impr... Read More about Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization.

Responsible Design & Evaluation of a Conversational Agent for a National Careers Service (2023)
Presentation / Conference Contribution
Wilson, M., Cruickshank, P., Gkatzia, D., & Robertson, P. (2023, September). Responsible Design & Evaluation of a Conversational Agent for a National Careers Service. Presented at Symposium on Future Directions in Information Access (FDIA) 2023, Vienna, Austria

This PhD project applies a research-through-design approach to the development of a conversational agent for a national career service for young people. This includes addressing practical, interactional and ethical aspects of the system. For each asp... Read More about Responsible Design & Evaluation of a Conversational Agent for a National Careers Service.

Expressive Talking Avatars (2024)
Journal Article
Pan, Y., Tan, S., Cheng, S., Lin, Q., Zeng, Z., & Mitchell, K. (2024). Expressive Talking Avatars. IEEE Transactions on Visualization and Computer Graphics, 30(5), 2538-2548. https://doi.org/10.1109/TVCG.2024.3372047

Stylized avatars are common virtual representations used in VR to support interaction and communication between remote collaborators. However, explicit expressions are notoriously difficult to create, mainly because most current methods rely on geome... Read More about Expressive Talking Avatars.