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Outputs (663)

Multiclass-SGCN: Sparse Graph-based Trajectory Prediction with Agent Class Embedding (2022)
Presentation / Conference Contribution
Li, R., Katsigiannis, S., & Shum, H. P. (2022). Multiclass-SGCN: Sparse Graph-based Trajectory Prediction with Agent Class Embedding. In 2022 IEEE International Conference on Image Processing (ICIP) Proceedings (2346-2350). https://doi.org/10.1109/icip46576.2022.9897644

Trajectory prediction of road users in real-world scenarios is challenging because their movement patterns are stochastic and complex. Previous pedestrian-oriented works have been successful in modelling the complex interactions among pedestrians, bu... Read More about Multiclass-SGCN: Sparse Graph-based Trajectory Prediction with Agent Class Embedding.

Latent Bernoulli Autoencoder (2019)
Presentation / Conference Contribution
Fajtl, J., Argyriou, V., Monekosso, D., & Remagnino, P. (2019). Latent Bernoulli Autoencoder.

Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification (2022)
Presentation / Conference Contribution
Bevan, P., & Atapour-Abarghouei, A. (2022). Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification. In K. Chaudhuri, S. Jegelka, L. Song, C. Szepesvari, G. Niu, & S. Sabato (Eds.), Proceedings of Machine Learning Research (1874-1892)

Convolutional Neural Networks have demonstrated dermatologist-level performance in the classification of melanoma and other skin lesions, but prediction irregularities due to biases seen within the training data are an issue that should be addressed... Read More about Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification.

D'OraCa: Deep Learning-Based Classification of Oral Lesions with Mouth Landmark Guidance for Early Detection of Oral Cancer (2021)
Presentation / Conference Contribution
Lim, J. H., Tan, C. S., Chan, C. S., Welikala, R. A., Remagnino, P., Rajendran, S., …Barman, S. A. (2021). D'OraCa: Deep Learning-Based Classification of Oral Lesions with Mouth Landmark Guidance for Early Detection of Oral Cancer. In B. Papiez, M. Yaqub, J. Jiao, A. Namburete, & J. Noble (Eds.), Medical Image Understanding and Analysis 25th Annual Conference, MIUA 2021, Oxford, United Kingdom, July 12–14, 2021, Proceedings (408-422). https://doi.org/10.1007/978-3-030-80432-9_31

COSΦ: Artificial pheromone system for robotic swarms research (2015)
Presentation / Conference Contribution
Arvin, F., Krajnik, T., Turgut, A. E., & Yue, S. (2015). COSΦ: Artificial pheromone system for robotic swarms research. . https://doi.org/10.1109/iros.2015.7353405

Pheromone-based communication is one of the most effective ways of communication widely observed in nature. It is particularly used by social insects such as bees, ants and termites; both for inter-agent and agent-swarm communications. Due to its eff... Read More about COSΦ: Artificial pheromone system for robotic swarms research.

Efficient Uncertainty Quantification for Multilabel Text Classification (2022)
Presentation / Conference Contribution
Yu, J., Cristea, A. I., Harit, A., Sun, Z., Aduragba, O. T., Shi, L., & Al Moubayed, N. (2022). Efficient Uncertainty Quantification for Multilabel Text Classification. . https://doi.org/10.1109/ijcnn55064.2022.9892871

Despite rapid advances of modern artificial intelligence (AI), there is a growing concern regarding its capacity to be explainable, transparent, and accountable. One crucial step towards such AI systems involves reliable and efficient uncertainty qua... Read More about Efficient Uncertainty Quantification for Multilabel Text Classification.

Contrastive Learning with Heterogeneous Graph Attention Networks on Short Text Classification (2022)
Presentation / Conference Contribution
Sun, Z., Harit, A., Cristea, A. I., Yu, J., Shi, L., & Al Moubayed, N. (2022). Contrastive Learning with Heterogeneous Graph Attention Networks on Short Text Classification. . https://doi.org/10.1109/ijcnn55064.2022.9892257

Graph neural networks (GNNs) have attracted extensive interest in text classification tasks due to their expected superior performance in representation learning. However, most existing studies adopted the same semi-supervised learning setting as the... Read More about Contrastive Learning with Heterogeneous Graph Attention Networks on Short Text Classification.

Geometric Features Informed Multi-person Human-object Interaction Recognition in Videos (2022)
Presentation / Conference Contribution
Qiao, T., Men, Q., Li, F. W., Kubotani, Y., Morishima, S., & Shum, H. P. (2022). Geometric Features Informed Multi-person Human-object Interaction Recognition in Videos. . https://doi.org/10.1007/978-3-031-19772-7_28

Human-Object Interaction (HOI) recognition in videos is important for analysing human activity. Most existing work focusing on visual features usually suffer from occlusion in the real-world scenarios. Such a problem will be further complicated when... Read More about Geometric Features Informed Multi-person Human-object Interaction Recognition in Videos.

Cross-modal Image Synthesis in Dual-Energy X-Ray Security Imagery (2022)
Presentation / Conference Contribution
Isaac-Medina, B., Bhowmik, N., Willcocks, C., & Breckon, T. (2022). Cross-modal Image Synthesis in Dual-Energy X-Ray Security Imagery. . https://doi.org/10.1109/cvprw56347.2022.00048

Dual-energy X-ray scanners are used for aviation security screening given their capability to discriminate materials inside passenger baggage. To facilitate manual operator inspection, a pseudo-colouring is assigned to the effective composition of th... Read More about Cross-modal Image Synthesis in Dual-Energy X-Ray Security Imagery.

Adaptive optical methods for in vivo imaging in developing Zebra fish (2012)
Presentation / Conference Contribution
Girkin, J., Taylor, J., Bourgenot, C., Saunter, C., & Love, G. (2012). Adaptive optical methods for in vivo imaging in developing Zebra fish. In 2012 International Symposium on Optomechatronic Technologies (ISOT 2012). https://doi.org/10.1109/isot.2012.6403295

The humble Zebra fish is rapidly establishing itself as the model of choice for a wide range of biological investigations, in particular at the developing embryo stage. Single Plane Illumination Microscopy (SPIM) has already been shown to be a very p... Read More about Adaptive optical methods for in vivo imaging in developing Zebra fish.

Omnipotent Virtual Giant for Remote Human–Swarm Interaction (2021)
Presentation / Conference Contribution
Jang, I., Hu, J., Arvin, F., Carrasco, J., & Lennox, B. (2021). Omnipotent Virtual Giant for Remote Human–Swarm Interaction. . https://doi.org/10.1109/ro-man50785.2021.9515542

This paper proposes an intuitive human-swarm interaction framework inspired by our childhood memory in which we interacted with living ants by changing their positions and environments as if we were omnipotent relative to the ants. In virtual reality... Read More about Omnipotent Virtual Giant for Remote Human–Swarm Interaction.