| Emission quantification via passive infrared optical gas imaging: A review R Kang, P Liatsis, DC Kyritsis Energies 15 (9), 3304, 2022 | 21 | 2022 |
| 齿轮传动对转桨扇发动机总体性能建模 康瑞元， 陈玉春， 蔡飞超， 黄兴， 陈凤萍 推进技术 40 (11), 2428-2435, 2019 | 8 | 2019 |
| Self-validated physics-embedding network: A general framework for inverse modelling R Kang, DC Kyritsis, P Liatsis arXiv preprint arXiv:2210.06071, 2022 | 7 | 2022 |
| Performance Modelling of Geared Contra-RotatingPropfan Engine K Rui-yuan, C Yu-chun, CAI Fei-chao, H Xing, C Feng-ping Journal of Propulsion Technology 40 (11), 2428, 2019 | 6 | 2019 |
| Design of a triple combined cycle engine Y Gao, Y Chen, L Jia, R Kang 21st AIAA International Space Planes and Hypersonics Technologies Conference …, 2017 | 3 | 2017 |
| Physics-Driven ML-Based Modelling for Correcting Inverse Estimation R Kang, T Mu, P Liatsis, DC Kyritsis NeurIPS 2023, 2023 | 2 | 2023 |
| Intelligence against complexity: Machine learning for nonuniform temperature-field measurements through laser absorption R Kang, DC Kyritsis, P Liatsis Plos one 17 (12), e0278885, 2022 | 2 | 2022 |
| Performance Calculation and Integrated Mission Assessment of High Speed Turbojet-Scramjet Combined Engine K Rui-yuan, C Yu-chun, GAO Yuan 2018 9th International Conference on Mechanical and Aerospace Engineering …, 2018 | 2 | 2018 |
| Flame-state monitoring based on very low number of visible or infrared images via few-shot learning R Kang, P Liatsis, DC Kyritsis arXiv preprint arXiv:2210.07845, 2022 | 1 | 2022 |
| Physics-Driven AI Correction in Laser Absorption Sensing Quantification R Kang, P Liatsis, M Geng, Q Yang arXiv preprint arXiv:2408.10714, 2024 | | 2024 |
| EEE, Remediating the failure of machine learning models via a network-based optimization patch R Kang, D Kyritsis, P Liatsis arXiv preprint arXiv:2304.11321, 2023 | | 2023 |
| Utilizing domain knowledge to enhance the performance of deep learning model on quantifying composition ratio from visual images of flames R Kang, P Liatsis, DC Kyritsis | | 2023 |
| Spatially-resolved Thermometry from Line-of-Sight Emission Spectroscopy via Machine Learning R Kang, DC Kyritsis, P Liatsis arXiv preprint arXiv:2212.07836, 2022 | | 2022 |
| Quantifying Line-of-Sight Profile Nonuniformity Effect on Laser Absorption Spectroscopy Temperature Measurement via Data Analysis K Ruiyuan, P Liatsis, DC Kyritsis Fluids Engineering Division Summer Meeting 85833, V001T02A006, 2022 | | 2022 |
| Emission Quantification via Passive Infrared Optical Gas Imaging: A Review. Energies 2022, 15, 3304 R Kang, P Liatsis, DC Kyritsis s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2022 | | 2022 |
| Realizing Flame State Monitoring with Very Few Visual or Infrared Images via Few-Shot Learning. R Kang, P Liatsis, DC Kyritsis CoRR, 2022 | | 2022 |
| Research of a Triple Combined Cycle Engine Design Y Gao, Y Chen, L Jia, R Kang | | 2017 |
| A Data-Driven Method for Spatially-Resolved Thermometry from Line-of-Sight Emission Spectroscopy R Kang, DC Kyritsis, P Liatsis Available at SSRN 4310971, 0 | | |
Panos LiatsisProfessor, Khalifa University在 ku.ac.ae 的电子邮件经过验证
Panos LiatsisProfessor, Khalifa University在 ku.ac.ae 的电子邮件经过验证
Dimitrios KyritsisAssociate Dean for Academic Affairs, College of Technology and Design, NEOM University在 neom.com 的电子邮件经过验证