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Outputs (119)

Recognising Human-Object Interactions Using Attention-based LSTMs (2019)
Presentation / Conference Contribution
Almushyti, M., & Li, F. W. (2019). Recognising Human-Object Interactions Using Attention-based LSTMs. In F. P. Vidal, G. K. . L. Tam, & J. C. Roberts (Eds.), Computer Graphics and Visual Computing (CGVC) (135-139). https://doi.org/10.2312/cgvc.20191269

Recognising Human-object interactions (HOIs) in videos is a challenge task especially when a human can interact with multiple objects. This paper attempts to solve the problem of HOIs by proposing a hierarchical framework that analyzes human-object i... Read More about Recognising Human-Object Interactions Using Attention-based LSTMs.

Narrative for Gamification in Education: Why Should you Care? (2019)
Presentation / Conference Contribution
Toledo Palomino, P., Toda, A. M., Oliveira, W., Cristea, A. I., & Isotani, S. (2019). Narrative for Gamification in Education: Why Should you Care?. . https://doi.org/10.1109/icalt.2019.00035

Gamification applied to education studies are focusing to encourage students to perform specific tasks, however many of these studies are still inconclusive about how much gamification can influence engagement. Also, the frameworks used to apply gami... Read More about Narrative for Gamification in Education: Why Should you Care?.

Early Performance Prediction for CS1 Course Students using a Combination of Machine Learning and an Evolutionary Algorithm (2019)
Presentation / Conference Contribution
Pereira, F. D., Oliveira, E. H., Fernandes, D., & Cristea, A. (2019). Early Performance Prediction for CS1 Course Students using a Combination of Machine Learning and an Evolutionary Algorithm. . https://doi.org/10.1109/icalt.2019.00066

Many researchers have started extracting student behaviour by cleaning data collected from web environments and using it as features in machine learning (ML) models. Using log data collected from an online judge, we have compiled a set of successful... Read More about Early Performance Prediction for CS1 Course Students using a Combination of Machine Learning and an Evolutionary Algorithm.

To complete or to estimate, that is the question: A Multi-Task Depth Completion and Monocular Depth Estimation (2019)
Presentation / Conference Contribution
Atapour-Abarghouei, A., & Breckon, T. P. (2019). To complete or to estimate, that is the question: A Multi-Task Depth Completion and Monocular Depth Estimation. In Proceedings of 2019 International Conference on 3D Vision (3DV) (183-193). https://doi.org/10.1109/3dv.2019.00029

Robust three-dimensional scene understanding is now an ever-growing area of research highly relevant in many real-world applications such as autonomous driving and robotic navigation. In this paper, we propose a multi-task learning-based model capabl... Read More about To complete or to estimate, that is the question: A Multi-Task Depth Completion and Monocular Depth Estimation.

A Ranking based Attention Approach for Visual Tracking (2019)
Presentation / Conference Contribution
Peng, S., Kamata, S., & Breckon, T. (2019). A Ranking based Attention Approach for Visual Tracking. In 2019 IEEE International Conference on Image Processing (ICIP) ; proceedings (3073-3077). https://doi.org/10.1109/icip.2019.8803358

Correlation filters (CF) combined with pre-trained convolutional neural network (CNN) feature extractors have shown an admirable accuracy and speed in visual object tracking. However, existing CNN-CF based methods still suffer from the background int... Read More about A Ranking based Attention Approach for Visual Tracking.

Monocular Segment-Wise Depth: Monocular Depth Estimation Based on a Semantic Segmentation Prior (2019)
Presentation / Conference Contribution
Atapour-Abarghouei, A., & Breckon, T. (2019). Monocular Segment-Wise Depth: Monocular Depth Estimation Based on a Semantic Segmentation Prior. In 2019 IEEE International Conference on Image Processing (ICIP) ; proceedings (4295-4299). https://doi.org/10.1109/icip.2019.8803551

Monocular depth estimation using novel learning-based approaches has recently emerged as a promising potential alternative to more conventional 3D scene capture technologies within real-world scenarios. Many such solutions often depend on large quant... Read More about Monocular Segment-Wise Depth: Monocular Depth Estimation Based on a Semantic Segmentation Prior.

Deep Blind Synthesized Image Quality Assessment with Contextual Multi-Level Feature Pooling (2019)
Presentation / Conference Contribution
Wang, X., Wang, K., Yang, B., Li, F. W., & Liang, X. (2019). Deep Blind Synthesized Image Quality Assessment with Contextual Multi-Level Feature Pooling. In 2019 IEEE International Conference on Image Processing Proceedings (435-439). https://doi.org/10.1109/icip.2019.8802943

Blind image quality metrics have achieved significant improvement on traditional 2D image dataset, yet still being insufficient for evaluating synthesized images generated from depth-image-based rendering. The geometric distortions in synthesized ima... Read More about Deep Blind Synthesized Image Quality Assessment with Contextual Multi-Level Feature Pooling.

Deleting edges to restrict the size of an epidemic in temporal networks (2019)
Presentation / Conference Contribution
Enright, J., Meeks, K., Mertzios, G., & Zamaraev, V. (2019). Deleting edges to restrict the size of an epidemic in temporal networks. In P. Rossmanith, P. Heggernes, & J. Katoen (Eds.), 44th International Symposium on Mathematical Foundations of Computer Science (57:1-57:15). https://doi.org/10.4230/lipics.mfcs.2019.57

Spreading processes on graphs are a natural model for a wide variety of real-world phenomena, including information or behaviour spread over social networks, biological diseases spreading over contact or trade networks, and the potential flow of good... Read More about Deleting edges to restrict the size of an epidemic in temporal networks.