| A part-aware multi-scale fully convolutional network for pedestrian detection P Yang, G Zhang, L Wang, L Xu, Q Deng, MH Yang IEEE Transactions on Intelligent Transportation Systems 22 (2), 1125-1137, 2020 | 59 | 2020 |
| Hardhat-wearing detection based on a lightweight convolutional neural network with multi-scale features and a top-down module L Wang, L Xie, P Yang, Q Deng, S Du, L Xu Sensors 20 (7), 1868, 2020 | 27 | 2020 |
| Local path integration for attribution P Yang, N Akhtar, Z Wen, A Mian AAAI Conference on Artificial Intelligence (AAAI) 37 (3), 3173-3180, 2023 | 8 | 2023 |
| Re-calibrating Feature Attributions for Model Interpretation P Yang, N Akhtar, Z Wen, M Shah, AS Mian International Conference on Learning Representations (ICLR), 2023 | 4 | 2023 |
| Multi-grained interpre table network for image recognition P Yang, Z Wen, A Mian 2022 26th International Conference on Pattern Recognition (ICPR), 3815-3821, 2022 | 2 | 2022 |
| A local top-down module for object detection with multi-scale features S Huang, L Wang, P Yang, Q Deng Pattern Recognition and Computer Vision: First Chinese Conference, PRCV 2018 …, 2018 | 1 | 2018 |
| Fast-PGM: Fast Probabilistic Graphical Model Learning and Inference J Jiang, Z Wen, P Yang, A Mansoor, A Mian arXiv preprint arXiv:2405.15605, 2024 | | 2024 |
| Backdoor-based Explainable AI Benchmark for High Fidelity Evaluation of Attribution Methods P Yang, N Akhtar, J Jiang, A Mian arXiv preprint arXiv:2405.02344, 2024 | | 2024 |
| Visible part prediction and temporal calibration for pedestrian detection P Yang, W Li, L Wang, L Xu, Q Deng IET Image Processing 17 (1), 42-56, 2023 | | 2023 |
| A Backdoor-based Explainable AI Benchmark for Improved Fidelity in Evaluating Attribution Methods P Yang, N AKHTAR, J Jiang, AS Mian | | |
| Regulating Model Reliance on Non-Robust Features by Smoothing Marginal Density of Input P Yang, N AKHTAR, M Shah, AS Mian | | |
Ajmal Saeed MianProfessor at The University of Western Australia在 uwa.edu.au 的电子邮件经过验证
