-
Li, X., Nabati, R., Singh, K., Corona, E., Metsis, V., & Parchami, A. (2023). EMOD: Efficient Moving Object Detection via Image Eccentricity Analysis and Sparse Neural Networks. In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops (pp. 51–59). IEEE Xplore. https://doi.org/https://doi.org/10.1109/WACVW58289.2023.00010
-
Atkinson, G. M., Li, X., & Metsis, V. (2023). Conditional Diffusion with Label Smoothing for Data Synthesis from Examples with Noisy Labels. In 31st European Signal Processing Conference (EUSIPCO 2023) (pp. 1300–1304). IEEE. https://doi.org/10.23919/EUSIPCO58844.2023.10289794
-
Li, X., Metsis, V., & Ngu, A. H. (2023). Generating Realistic Multi-class Biosignals with BioSGAN: A Transformer-based Label-guided Generative Adversarial Network. In The 25th International Conference on Artificial Intelligence (ICAI’23). USA: IEEE.
-
Li, X., Metsis, V., Wang, H., & Ngu, H. H. (2022). TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network. https://doi.org/0.1007/978-3-031-09342-5_13
-
Li, X., & Metsis, V. (2022). SPP-EEGNET: An Input-Agnostic Self-supervised EEG Representation Model for Inter-dataset Transfer Learning. In 18th International Conference on Computing and Information Technology (IC2IT 2022). Springer. https://doi.org/https://doi.org/10.1007/978-3-030-99948-3_17
