All Outputs (2740)

Swarm flocking using optimisation for a self-organised collective motion (2024)
Journal Article
Bahaidarah, M., Rekabi-Bana, F., Marjanovic, O., & Arvin, F. (2024). Swarm flocking using optimisation for a self-organised collective motion. Swarm and Evolutionary Computation, 86, Article 101491. https://doi.org/10.1016/j.swevo.2024.101491

Collective motion, often called flocking, is a prevalent behaviour observed in nature wherein large groups of organisms move cohesively, guided by simple local interactions, as exemplified by bird flocks and fish schools. Inspired by those intelligen... Read More about Swarm flocking using optimisation for a self-organised collective motion.

Multiview latent space learning with progressively fine-tuned deep features for unsupervised domain adaptation (2024)
Journal Article
Zhu, C., Wang, Q., Xie, Y., & Xu, S. (2024). Multiview latent space learning with progressively fine-tuned deep features for unsupervised domain adaptation. Information Sciences, 662, Article 120223. https://doi.org/10.1016/j.ins.2024.120223

Unsupervised Domain Adaptation (UDA) and Multi-source Domain Adaptation (MDA) have emerged as practical techniques to address the domain shift between source and target domains with different statistical distributions, where the target domain often h... Read More about Multiview latent space learning with progressively fine-tuned deep features for unsupervised domain adaptation.

A multiscale optimisation algorithm for shape and material reconstruction from a single X-ray image (2024)
Presentation / Conference Contribution
Westmacott, H., Ivrissimtzis, I., & Weinzierl, T. (2024). A multiscale optimisation algorithm for shape and material reconstruction from a single X-ray image. In ICIGP '24: Proceedings of the 2024 7th International Conference on Image and Graphics Processing (252-259). https://doi.org/10.1145/3647649.3647690

We produce thickness and bone to soft tissue ratio estimations from a single, 2D medical X-ray image. For this, we simulate the scattering of the rays through a model of the object and embed this simulation into an optimiser which iteratively adjusts... Read More about A multiscale optimisation algorithm for shape and material reconstruction from a single X-ray image.

Parallel Derandomization for Coloring (2024)
Presentation / Conference Contribution
Coy, S., Czumaj, A., Davies-Peck, P., & Mishra, G. (2024, May). Parallel Derandomization for Coloring. Presented at 38th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2024), San Francisco

Graph coloring problems are among the most fundamental problems in parallel and distributed computing, and have been studied extensively in both settings. In this context, designing efficient deterministic algorithms for these problems has been found... Read More about Parallel Derandomization for Coloring.

Awake Complexity of Distributed Minimum Spanning Tree (2024)
Presentation / Conference Contribution
Augustine, J., Moses Jr, W. K., & Pandurangan, G. (in press). Awake Complexity of Distributed Minimum Spanning Tree.

The \emph{awake complexity} of a distributed algorithm measures the number of rounds in which a node is awake. When a node is not awake, it is {\em sleeping} and does not do any computation or communication and spends very little resources. Reduci... Read More about Awake Complexity of Distributed Minimum Spanning Tree.

All You Need are Random Walks: Fast and Simple Distributed Conductance Testing (2024)
Presentation / Conference Contribution
Batu, T., Trehan, A., & Trehan, C. (in press). All You Need are Random Walks: Fast and Simple Distributed Conductance Testing.

We propose a simple and time-optimal algorithm for property testing a graph for its conductance in the CONGEST model. Our algorithm takes only O(log n) rounds of communication (which is known to be optimal), and consists of simply running multiple ra... Read More about All You Need are Random Walks: Fast and Simple Distributed Conductance Testing.

Laplacian Projection Based Global Physical Prior Smoke Reconstruction (2024)
Journal Article
Xiao, S., Tong, C., Zhang, Q., Cen, Y., Li, F. W. B., & Liang, X. (2024). Laplacian Projection Based Global Physical Prior Smoke Reconstruction. IEEE Transactions on Visualization and Computer Graphics, https://doi.org/10.1109/tvcg.2024.3358636

We present a novel framework for reconstructing fluid dynamics in real-life scenarios. Our approach leverages sparse view images and incorporates physical priors across long series of frames, resulting in reconstructed fluids with enhanced physical c... Read More about Laplacian Projection Based Global Physical Prior Smoke Reconstruction.

Genome-Wide Identification of the ABC Gene Family and Its Expression in Response to the Wood Degradation of Poplar in Trametes gibbosa (2024)
Journal Article
Zhao, J., Wang, A., & Wang, Q. (in press). Genome-Wide Identification of the ABC Gene Family and Its Expression in Response to the Wood Degradation of Poplar in Trametes gibbosa. Journal of Fungi, 10(2), Article 96. https://doi.org/10.3390/jof10020096

Wood-rotting fungi’s degradation of wood not only facilitates the eco-friendly treatment of organic materials, decreasing environmental pollution, but also supplies crucial components for producing biomass energy, thereby reducing dependence on fossi... Read More about Genome-Wide Identification of the ABC Gene Family and Its Expression in Response to the Wood Degradation of Poplar in Trametes gibbosa.

Text mining for disease surveillance in veterinary clinical data: part one, the language of veterinary clinical records and searching for words (2024)
Journal Article
Davies, H., Nenadic, G., Alfattni, G., Arguello Casteleiro, M., Al Moubayed, N., Farrell, S. O., …Noble, P. M. (2024). Text mining for disease surveillance in veterinary clinical data: part one, the language of veterinary clinical records and searching for words. Frontiers in Veterinary Science, 11, Article 1352239. https://doi.org/10.3389/fvets.2024.1352239

The development of natural language processing techniques for deriving useful information from unstructured clinical narratives is a fast-paced and rapidly evolving area of machine learning research. Large volumes of veterinary clinical narratives no... Read More about Text mining for disease surveillance in veterinary clinical data: part one, the language of veterinary clinical records and searching for words.

Comparative Study of Face Tracking Algorithms for Remote Photoplethysmography (2024)
Presentation / Conference Contribution
Jayasinghe, J., Katsigiannis, S., & Malasinghe, L. (2024). Comparative Study of Face Tracking Algorithms for Remote Photoplethysmography. In 2023 International Conference on Electrical, Computer and Energy Technologies (ICECET). https://doi.org/10.1109/ICECET58911.2023.10389182

Remote Photoplethysmography (rPPG) is a non-invasive approach for monitoring Heart Rate (HR) that can be used in various applications in healthcare and biometrics. rPPG measurements acquired using facial videos have become very popular and one of the... Read More about Comparative Study of Face Tracking Algorithms for Remote Photoplethysmography.

Dispersion, Capacitated Nodes, and the Power of a Trusted Shepherd (2024)
Presentation / Conference Contribution
Moses Jr., W. K., & Redlich, A. (2024). Dispersion, Capacitated Nodes, and the Power of a Trusted Shepherd. In ICDCN '24: Proceedings of the 25th International Conference on Distributed Computing and Networking (400-405). https://doi.org/10.1145/3631461.3632310

In this paper, we look at and expand the problems of dispersion and Byzantine dispersion of mobile robots on a graph, introduced by Augustine and Moses Jr. [ICDCN 2018] and by Molla, Mondal, and Moses Jr. [ALGOSENSORS 2020], respectively, to graphs w... Read More about Dispersion, Capacitated Nodes, and the Power of a Trusted Shepherd.

SecureFlow: Knowledge and data-driven ensemble for intrusion detection and dynamic rule configuration in software-defined IoT environment (2024)
Journal Article
Singh, A., Chouhan, P. K., & Aujla, G. S. (2024). SecureFlow: Knowledge and data-driven ensemble for intrusion detection and dynamic rule configuration in software-defined IoT environment. Ad Hoc Networks, 156, Article 103404. https://doi.org/10.1016/j.adhoc.2024.103404

There is a massive growth in the rate of heterogeneous devices configured in the Internet of Things (IoT) environment for efficient communication. The IoT devices are limited in resources, and there are no defined protocols in terms of security durin... Read More about SecureFlow: Knowledge and data-driven ensemble for intrusion detection and dynamic rule configuration in software-defined IoT environment.

Pose-based tremor type and level analysis for Parkinson’s disease from video (2024)
Journal Article
Zhang, H., Ho, E. S. L., Zhang, X., Del Din, S., & Shum, H. P. H. (2024). Pose-based tremor type and level analysis for Parkinson’s disease from video. International Journal of Computer Assisted Radiology and Surgery, 19(5), 831-840. https://doi.org/10.1007/s11548-023-03052-4

Current methods for diagnosis of PD rely on clinical examination. The accuracy of diagnosis ranges between 73 and 84%, and is influenced by the experience of the clinical assessor. Hence, an automatic, effective and interpretable supporting system fo... Read More about Pose-based tremor type and level analysis for Parkinson’s disease from video.

∞-Diff: Infinite Resolution Diffusion with Subsampled Mollified States (2024)
Presentation / Conference Contribution
Bond-Taylor, S., & Willcocks, C. G. (2024, May). ∞-Diff: Infinite Resolution Diffusion with Subsampled Mollified States. Presented at The International Conference on Learning Representations (ICLR), Vienna Austria

This paper introduces ∞-Diff, a generative diffusion model defined in an infinite-dimensional Hilbert space, which can model infinite resolution data. By training on randomly sampled subsets of coordinates and denoising content only at those location... Read More about ∞-Diff: Infinite Resolution Diffusion with Subsampled Mollified States.

HSE: Hybrid Species Embedding for Deep Metric Learning (2024)
Presentation / Conference Contribution
Yang, B., Sun, H., Li, F. W. B., Chen, Z., Cai, J., & Song, C. (2024). HSE: Hybrid Species Embedding for Deep Metric Learning. In 2023 IEEE/CVF International Conference on Computer Vision (ICCV). https://doi.org/10.1109/ICCV51070.2023.01014

Deep metric learning is crucial for finding an embedding function that can generalize to training and testing data, including unknown test classes. However, limited training samples restrict the model's generalization to downstream tasks. While addin... Read More about HSE: Hybrid Species Embedding for Deep Metric Learning.

Depth lower bounds in Stabbing Planes for combinatorial principles (2024)
Journal Article
Dantchev, S., Galesi, N., Ghani, A., & Martin, B. (2024). Depth lower bounds in Stabbing Planes for combinatorial principles. Logical Methods in Computer Science, 20(1), 1-19. https://doi.org/10.46298/lmcs-20%281%3A1%292024

Stabbing Planes (also known as Branch and Cut) is a proof system introduced very recently which, informally speaking, extends the DPLL method by branching on integer linear inequalities instead of single variables. The techniques known so far to prov... Read More about Depth lower bounds in Stabbing Planes for combinatorial principles.

A survey on vulnerability of federated learning: A learning algorithm perspective (2024)
Journal Article
Xie, X., Hu, C., Ren, H., & Deng, J. (2024). A survey on vulnerability of federated learning: A learning algorithm perspective. Neurocomputing, 573, Article 127225. https://doi.org/10.1016/j.neucom.2023.127225

Federated Learning (FL) has emerged as a powerful paradigm for training Machine Learning (ML), particularly Deep Learning (DL) models on multiple devices or servers while maintaining data localized at owners’ sites. Without centrali... Read More about A survey on vulnerability of federated learning: A learning algorithm perspective.

PRIMM and Proper: Authentic Investigation in HE Introductory Programming with PeerWise and GitHub (2024)
Presentation / Conference Contribution
Bradley, S., & Ramezani, A. (2024). PRIMM and Proper: Authentic Investigation in HE Introductory Programming with PeerWise and GitHub. In CEP '24: Proceedings of the 8th Conference on Computing Education Practice (33-36). https://doi.org/10.1145/3633053.3633062

We explore the use of the PRIMM methodology (Predict, Run, Investigate, Modify, Make) within a higher education introductory programming setting, particularly focusing on the three first three steps. Formative prediction questions on the effects of c... Read More about PRIMM and Proper: Authentic Investigation in HE Introductory Programming with PeerWise and GitHub.

Dual RIS-aided Parallel Intelligence Surface for IoAMVSs: A Co-Design Approach for 3C Problems (2024)
Journal Article
Bo, P., Tu, W., Tu, X., Qu, F., & Wang, F. (2024). Dual RIS-aided Parallel Intelligence Surface for IoAMVSs: A Co-Design Approach for 3C Problems. IEEE Transactions on Intelligent Vehicles, https://doi.org/10.1109/tiv.2023.3348996

The internet of autonomous marine vehicle systems (IoAMVSs) requires ultra-reliable communications, ultra-real-time control, and ultra-high precision computation. Classical parallel intelligence theory is a popular method for developing IoAMVSs in th... Read More about Dual RIS-aided Parallel Intelligence Surface for IoAMVSs: A Co-Design Approach for 3C Problems.

Tackling Data Bias in Painting Classification with Style Transfer (2023)
Presentation / Conference Contribution
Vijendran, M., Li, F. W., & Shum, H. P. (2023). Tackling Data Bias in Painting Classification with Style Transfer. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5 VISAPP: VISAPP (250-261). https://doi.org/10.5220/0011776600003417

It is difficult to train classifiers on paintings collections due to model bias from domain gaps and data bias from the uneven distribution of artistic styles. Previous techniques like data distillation, traditional data augmentation and style transf... Read More about Tackling Data Bias in Painting Classification with Style Transfer.