Zhang, L., Liu, Z., Zhang, S., Yang, X., Qiao, H., Huang, K., & Hussain, A. (2019). Cross-modality interactive attention network for multispectral pedestrian detection. Information Fusion, 50, 20-29. https://doi.org/10.1016/j.inffus.2018.09.015
Multispectral pedestrian detection is an emerging solution with great promise in many around-the-clock applications, such as automotive driving and security surveillance. To e...
Kobayashi, S., Kane, T., & Paton, C. (2018). The Privacy and Security Implications of Open Data in Healthcare: A Contribution from the IMIA Open Source Working Group. IMIA Yearbook of Medical Informatics, doi:10.1055/s-0038-1641201. ISSN 0943-4747
Objective: The International Medical Informatics Association (IMIA) Open Source Working Group (OSWG) initiated a group discussion to discuss current privacy and security issue...
Peng, T., & Telle, A. (2018). A tool for generating synthetic data. In DATA '18 Proceedings of the First International Conference on Data Science, E-learning and Information Systemsdoi:10.1145/3279996.3280018
Bartie, P., Mackaness, W., Gkatzia, D. & Rieser, V. (2015). The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes. In 10th International Conference on Language Resources and Evaluation (LREC)ISBN 978-2-9517408-9-1
We present a newly crowd-sourced data set of natural language references to objects anchored in complex urban scenes (In short: The REAL Corpus – Referring Expressions Anchore...
Gkatzia, D., Rieser, V., Bartie, P., & Mackaness, W. (2015). From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 1936-1942. https://doi.org/10.18653/v1/d15-1224
Predicting the success of referring expressions (RE) is vital for real world applications such as navigation systems. Traditionally, research has focused on studying Referring...
Gkatzia, D., Cercas Curry, A., Rieser, V., & Lemon, O. (2015). A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation. In Proceedings of the 15th European Workshop on Natural Language Generation, 112-113. https://doi.org/10.18653/v1/w15-4720
Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores, such as probabilities. A concrete example of such data is weather data. We w...
Gkatzia, D., & Mahamood, S. (2015). A Snapshot of NLG Evaluation Practices 2005 - 2014. https://doi.org/10.18653/v1/w15-4708
In this paper we present a snapshot of endto-end NLG system evaluations as presented in conference and journal papers1 over the last ten years in order to better understand th...
Cercas Curry, A., Gkatzia, D., & Rieser, V. (2015). Generating and Evaluating Landmark-Based Navigation Instructions in Virtual Environments. In Proceedings of the 15th European Workshop on Natural Language Generation, 90-94. https://doi.org/10.18653/v1/w15-4715
Referring to landmarks has been identified to lead to improved navigation instructions. However, a previous corpus study suggests that human “wizards” also choose to refer to ...
Gkatzia, D., Hastie, H., & Lemon, O. (2014). Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data. In Proceedings of the Conference Volume 1: Long Papers, 1231-1240. https://doi.org/10.3115/v1/p14-1116
We present a novel approach for automatic report generation from time-series data, in the context of student feedback generation. Our proposed methodology treats content selec...
Shen, Q., Peng, T., & Milne, R. (1998). Dimensional analysis based causal ordering. In Proceedings of the 13th International Workshop on Qualitative Reasoning, 193-202
This paper presents a novel approach for generating causal dependencies between system variables, from an acausal description of the system behaviour, and for identifying the ...
Knight, B., Ma, J., & Peng, T. (1996). A discrete formalism for reasoning about action and change. In R. Adey, G. Rzevski, & R. Teti (Eds.), Applications of artificial intelligence in engineering XIIdoi:10.2495/AI970101
No abstract available.