| Real-time detection of railway track component via one-stage deep learning networks T Wang, F Yang, KL Tsui Sensors 20 (15), 4325, 2020 | 55 | 2020 |
| A deep generative approach for rail foreign object detections via semisupervised learning T Wang, Z Zhang, KL Tsui IEEE Transactions on Industrial Informatics 19 (1), 459-468, 2022 | 36 | 2022 |
| A deep-learning-powered near-real-time detection of railway track major components: A two-stage computer-vision-based method L Zhuang, H Qi, T Wang, Z Zhang IEEE Internet of Things Journal 9 (19), 18806-18816, 2022 | 16 | 2022 |
| Automatic rail component detection based on AttnConv-Net T Wang, Z Zhang, F Yang, KL Tsui IEEE Sensors Journal 22 (3), 2379-2388, 2021 | 15 | 2021 |
| Intelligent railway foreign object detection: A semi-supervised convolutional autoencoder based method T Wang, Z Zhang, F Yang, KL Tsui arXiv preprint arXiv:2108.02421, 2021 | 12 | 2021 |
| PSTN: periodic spatial-temporal deep neural network for traffic condition prediction T Wang, Z Zhang, KL Tsui arXiv preprint arXiv:2108.02424, 2021 | 7 | 2021 |
| PFFN: Periodic feature-folding deep neural network for traffic condition forecasting T Wang, Z Zhang, KL Tsui IEEE Internet of Things Journal, 2023 | 5 | 2023 |
| Automatic Detection of Rail Components via A Deep Convolutional Transformer Network T Wang, Z Zhang, F Yang, KL Tsui arXiv e-prints, arXiv: 2108.02423, 2021 | 4 | 2021 |
