| Smart factory of industry 4.0: Key technologies, application case, and challenges B Chen, J Wan, L Shu, P Li, M Mukherjee, B Yin Ieee Access 6, 6505-6519, 2017 | 1514 | 2017 |
| An accurate detection for dynamic liquid level based on MIMO ultrasonic transducer array P Li, Y Cai, X Shen, S Nabuzaale, J Yin, J Li IEEE Transactions on Instrumentation and Measurement 64 (3), 582-595, 2014 | 109 | 2014 |
| Fault knowledge transfer assisted ensemble method for remaining useful life prediction P Xia, Y Huang, P Li, C Liu, L Shi IEEE Transactions on Industrial Informatics 18 (3), 1758-1769, 2021 | 75 | 2021 |
| Cross-network fusion and scheduling for heterogeneous networks in smart factory J Wan, J Yang, S Wang, D Li, P Li, M Xia IEEE Transactions on Industrial Informatics 16 (9), 6059-6068, 2019 | 47 | 2019 |
| Data Driven Modeling for System-Level Condition Monitoring on Wind Power Plants. J Eickmeyer, P Li, O Givehchi, F Pethig, O Niggemann DX, 43-50, 2015 | 28 | 2015 |
| Non-convex hull based anomaly detection in CPPS P Li, O Niggemann Engineering Applications of Artificial Intelligence 87, 103301, 2020 | 21 | 2020 |
| MFGAN: Multi feature guided aggregation network for remote sensing image S Chu, P Li, M Xia Neural Computing and Applications 34 (12), 10157-10173, 2022 | 16 | 2022 |
| Improving clustering based anomaly detection with concave hull: An application in fault diagnosis of wind turbines P Li, O Niggemann 2016 IEEE 14th International Conference on Industrial Informatics (INDIN …, 2016 | 15 | 2016 |
| Data driven condition monitoring of wind power plants using cluster analysis P Li, J Eickmeyer, O Niggemann 2015 International Conference on Cyber-Enabled Distributed Computing and …, 2015 | 15 | 2015 |
| Trajectory shape analysis and anomaly detection utilizing information theory tools Y Guo, Q Xu, P Li, M Sbert, Y Yang Entropy 19 (7), 323, 2017 | 14 | 2017 |
| A structural developmental neural network with information saturation for continual unsupervised learning Z Ding, H Xie, P Li, X Xu CAAI Transactions on Intelligence Technology 8 (3), 780-795, 2023 | 12 | 2023 |
| A nonconvex archetypal analysis for one-class classification based anomaly detection in cyber-physical systems P Li, O Niggemann IEEE transactions on industrial informatics 17 (9), 6429-6437, 2020 | 12 | 2020 |
| Why symbolic ai is a key technology for self-adaption in the context of cpps A Bunte, P Wunderlich, N Moriz, P Li, A Mankowski, A Rogalla, ... 2019 24th IEEE International Conference on Emerging Technologies and Factory …, 2019 | 12 | 2019 |
| A geometric approach to clustering based anomaly detection for industrial applications P Li, O Niggemann, B Hammer IECON 2018-44th Annual Conference of the IEEE Industrial Electronics Society …, 2018 | 11 | 2018 |
| DBFGAN: Dual branch feature guided aggregation network for remote sensing image S Chu, P Li, M Xia, H Lin, M Qian, Y Zhang International Journal of Applied Earth Observation and Geoinformation 116 …, 2023 | 10 | 2023 |
| A selective fuzzy clustering ensemble algorithm K Li, P Li International Journal of Advanced Computer Research 3 (4), 1, 2013 | 10 | 2013 |
| A data provenance based architecture to enhance the reliability of data analysis for Industry 4.0 P Li, O Niggemann 2018 IEEE 23rd International Conference on Emerging Technologies and Factory …, 2018 | 9 | 2018 |
| Transformer in reinforcement learning for decision-making: a survey W Yuan, J Chen, S Chen, D Feng, Z Hu, P Li, W Zhao Frontiers of Information Technology & Electronic Engineering 25 (6), 763-790, 2024 | 8 | 2024 |
| Evo-maml: Meta-learning with evolving gradient J Chen, W Yuan, S Chen, Z Hu, P Li Electronics 12 (18), 3865, 2023 | 8 | 2023 |
| Fuzzy clustering with generalized entropy based on neural network K Li, P Li Unifying Electrical Engineering and Electronics Engineering: Proceedings of …, 2013 | 8 | 2013 |