Staff profile

Conference Paper

• Dur360BEV: A Real-world 360-degree Single Camera Dataset and Benchmark for Bird-Eye View Mapping in Autonomous Driving
  
  E, W., Yuan, C., Sun, Y., Gaus, Y., Atapour-Abarghouei, A., & Breckon, T. (in press). Dur360BEV: A Real-world 360-degree Single Camera Dataset and Benchmark for Bird-Eye View Mapping in Autonomous Driving. In Proceedings of the International Conference on Robotics and Automation 2025. IEEE Canada.
• KD360-VoxelBEV: LiDAR and 360-Degree Camera Cross Modality Knowledge Distillation for Bird’s-Eye-View Segmentation
  
  E, W., Sun, Y., Liu, J., Shum, H. P. H., Atapour-Abarghouei, A., & Breckon, T. P. (in press). KD360-VoxelBEV: LiDAR and 360-Degree Camera Cross Modality Knowledge Distillation for Bird’s-Eye-View Segmentation. Presented at The IEEE/CVF Winter Conference on Applications of Computer Vision 2026, Tucson, AZ, USA.
• Mind2Drive: Predicting Driver Intentions from EEG in Real-world On-Road Driving
  
  Alosaimi, G., Alhamdan, H., E, W., Katsigiannis, S., Atapour-Abarghouei, A., & Breckon, T. (in press). Mind2Drive: Predicting Driver Intentions from EEG in Real-world On-Road Driving. Presented at IEEE World Congress on Computational Intelligence (WCCI) - International Joint Conference on Neural Networks (IJCNN), Maastricht, The Netherlands.
• TOMD: A Trail-based Off-road Multimodal Dataset for Traversable Pathway Segmentation under Challenging Illumination Conditions
  
  Sun, Y., Li, L., E, W., Atapour-Abarghouei, A., & Breckon, T. (2025). TOMD: A Trail-based Off-road Multimodal Dataset for Traversable Pathway Segmentation under Challenging Illumination Conditions. In Proceedings of the International Joint Conference on Neural Networks. IEEE. https://doi.org/10.1109/IJCNN64981.2025.11229344