Outputs (3169)

Amnesia in the Atlantic: an AI Driven Serious Game on Marine Biodiversity (2021)
Presentation / Conference Contribution
Dionísio, M., Nisi, V., Xin, J., Bala, P., James, S., & Jardim Nunes, N. (2021, November). Amnesia in the Atlantic: an AI Driven Serious Game on Marine Biodiversity

The use of Conversational Interfaces has evolved rapidly in numerous fields; in particular, they are an interesting tool for Serious Games to leverage on. Conversational Interfaces can assist Serious Games’ goals, namely in presenting knowledge throu... Read More about Amnesia in the Atlantic: an AI Driven Serious Game on Marine Biodiversity.

Re-ID-AR: Improved Person Re-identification in Video via Joint Weakly Supervised Action Recognition (2021)
Presentation / Conference Contribution
Alsehaim, A., & Breckon, T. (2021, November). Re-ID-AR: Improved Person Re-identification in Video via Joint Weakly Supervised Action Recognition. Presented at BMVC 2021, Online

We uniquely consider the task of joint person re-identification (Re-ID) and action recognition in video as a multi-task problem. In addition to the broader potential of joint Re-ID and action recognition within the context of automated multi-camera s... Read More about Re-ID-AR: Improved Person Re-identification in Video via Joint Weakly Supervised Action Recognition.

Partitioning H-free graphs of bounded diameter (2021)
Presentation / Conference Contribution
Brause, C., Golovach, P. A., Martin, B., Paulusma, D., & Smith, S. (2021, December). Partitioning H-free graphs of bounded diameter. Presented at 32nd International Symposium on Algorithms and Computation (ISAAC 2021), Fukuoka, Japan

A natural way of increasing our understanding of NP-complete graph problems is to restrict the input to a special graph class. Classes of H-free graphs, that is, graphs that do not contain some graph H as an induced subgraph, have proven to be an ide... Read More about Partitioning H-free graphs of bounded diameter.

Energy Theft in Smart Grids: A Survey on Data-Driven Attack Strategies and Detection Methods (2021)
Journal Article
Althobaiti, A., Jindal, A., Marnerides, A. K., & Roedig, U. (2021). Energy Theft in Smart Grids: A Survey on Data-Driven Attack Strategies and Detection Methods. IEEE Access, 9, https://doi.org/10.1109/access.2021.3131220

Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark (2021)
Presentation / Conference Contribution
Isaac-Medina, B. K., Poyser, M., Organisciak, D., Willcocks, C. G., Breckon, T. P., & Shum, H. P. (2021, October). Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark. Presented at 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Montreal, BC, Canada

Unmanned Aerial Vehicles (UAV) can pose a major risk for aviation safety, due to both negligent and malicious use. For this reason, the automated detection and tracking of UAV is a fundamental task in aerial security systems. Common technologies for... Read More about Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark.

A Framework of Exercise Recommendation for Novice Learners in Computer Programming (2021)
Presentation / Conference Contribution
Na Nongkhai, L., Wang, J., & Mendori, T. (2021, November). A Framework of Exercise Recommendation for Novice Learners in Computer Programming. Presented at ICCE 2021: The 29th International Conference on Computers in Education, Online

To support novice learners majoring in Information Technology, this paper proposed an ontology-based framework to recommend exercise to learners in response to their understanding levels. This framework involves three essential mechanisms: (1) determ... Read More about A Framework of Exercise Recommendation for Novice Learners in Computer Programming.

How Can and Would People Protect From Online Tracking? (2021)
Journal Article
Mehrnezhad, M., Coopamootoo, K., & Toreini, E. (2022). How Can and Would People Protect From Online Tracking?. Proceedings on Privacy Enhancing Technologies, 1, 105-125. https://doi.org/10.2478/popets-2022-0006

Online tracking is complex and users find itchallenging to protect themselves from it. While the aca-demic community has extensively studied systems andusers for tracking practices, the link between the dataprotection regulations, websites’ practices... Read More about How Can and Would People Protect From Online Tracking?.

Clustering-based Redundancy Minimization for Edge Computing in Future Core Networks (2021)
Presentation / Conference Contribution
Perveen, A., Abozariba, R., Patwary, M., Aneiba, A., & Jindal, A. (2021, December). Clustering-based Redundancy Minimization for Edge Computing in Future Core Networks. Presented at 2021 IEEE 4th 5G World Forum (5GWF)

E2DA: Energy Efficient Data Aggregation and End-to-End Security in 3D Reconfigurable WSN (2021)
Journal Article
Ramasamy, K., Anisi, M. H., & Jindal, A. (2021). E2DA: Energy Efficient Data Aggregation and End-to-End Security in 3D Reconfigurable WSN. IEEE Transactions on Green Communications and Networking, 6(2), 787-798. https://doi.org/10.1109/tgcn.2021.3126786

High performance uncertainty quantification with parallelized multilevel Markov chain Monte Carlo (2021)
Presentation / Conference Contribution
Seelinger, L., Reinarz, A., Rannabauer, L., Bader, M., Bastian, P., & Scheichl, R. (2021, November). High performance uncertainty quantification with parallelized multilevel Markov chain Monte Carlo. Presented at SC21: International Conference for High Performance Computing, Networking, Storage and Analysis, St. Louis, MO

Numerical models of complex real-world phenomena often necessitate High Performance Computing (HPC). Uncertainties increase problem dimensionality further and pose even greater challenges. We present a parallelization strategy for multilevel Markov c... Read More about High performance uncertainty quantification with parallelized multilevel Markov chain Monte Carlo.