Dispersion of Mobile Robots
(2022)
Other
Molla, A. R., & Moses Jr., W. K. (2022). Dispersion of Mobile Robots
Outputs (220)
Intelligent Cyber-Physical Systems for Autonomous Transportation (2022)
Book
Garg, S., Aujla, G. S., Kaur, K., & Ahmed Shah, S. H. (Eds.). (2022). Intelligent Cyber-Physical Systems for Autonomous Transportation. Springer, Cham
Denoising Diffusion Probabilistic Models for Styled Walking Synthesis (2022)
Presentation / Conference Contribution
Findlay, E., Zhang, H., Chang, Z., & Shum, H. P. (2022, November). Denoising Diffusion Probabilistic Models for Styled Walking Synthesis. Presented at MIG 2022: The 15th Annual ACM SIGGRAPH Conference on Motion, Interaction and Games, Guanajuato, MexicoGenerating realistic motions for digital humans is time-consuming for many graphics applications. Data-driven motion synthesis approaches have seen solid progress in recent years through deep generative models. These results offer high-quality motion... Read More about Denoising Diffusion Probabilistic Models for Styled Walking Synthesis.
Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment (2022)
Presentation / Conference Contribution
Leach, A., Schmon, S. M., Degiacomi, M. T., & Willcocks, C. G. (2022, April). Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment. Presented at ICLR 2022 Workshop on Geometrical and Topological Representation LearningProbabilistic diffusion models are capable of modeling complex data distributions on high-dimensional Euclidean spaces for a range applications. However, many real world tasks involve more complex structures such as data distributions defined on mani... Read More about Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment.
An Almost Singularly Optimal Asynchronous Distributed MST Algorithm (2022)
Presentation / Conference Contribution
Dufoulon, F., Kutten, S., Moses Jr., W. K., Pandurangan, G., & Peleg, D. (2022, December). An Almost Singularly Optimal Asynchronous Distributed MST Algorithm. Presented at 36th International Symposium on Distributed Computing (DISC 2022)
Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets (2022)
Presentation / Conference Contribution
Battle, M. L., Atapour-Abarghouei, A., & McGough, A. S. (2022, December). Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets. Presented at 2022 IEEE International Conference on Big Data, Osaka, Japan
Information sharing practices during the COVID-19 pandemic: A case study about face masks (2022)
Journal Article
Baker, H., Concannon, S., & So, E. (2022). Information sharing practices during the COVID-19 pandemic: A case study about face masks. PLoS ONE, 17(5), https://doi.org/10.1371/journal.pone.0268043
Gamifying Experiential Learning Theory (2022)
Presentation / Conference Contribution
Alsaqqaf, A., & Li, F. W. (2022, December). Gamifying Experiential Learning Theory. Presented at International Conference On Web-Based Learning (ICWL 2022), Tenerife, Spain
UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery (2022)
Presentation / Conference Contribution
Organisciak, D., Poyser, M., Alsehaim, A., Hu, S., Isaac-Medina, B. K., Breckon, T. P., & Shum, H. P. UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery. Presented at 2022 17th International Conference on Computer Vision Theory and ApplicationsAs unmanned aerial vehicles (UAV) become more accessible with a growing range of applications, the risk of UAV disruption increases. Recent development in deep learning allows vision-based counter-UAV systems to detect and track UAVs with a single ca... Read More about UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery.
GANzzle: Reframing jigsaw puzzle solving as a retrieval task using generative mental images (2022)
Presentation / Conference Contribution
Talon, D., Del Bue, A., & James, S. (2022, October). GANzzle: Reframing jigsaw puzzle solving as a retrieval task using generative mental images. Presented at IEEE International Conference on Image Processing, Bordeaux, FrancePuzzle solving is a combinatorial challenge due to the difficulty of matching adjacent pieces. Instead, we infer a mental image from all pieces, which a given piece can then be matched against avoiding the combinatorial explosion. Exploiting advancem... Read More about GANzzle: Reframing jigsaw puzzle solving as a retrieval task using generative mental images.