| Explainable Deep Neural Networks for Multivariate Time Series Predictions R Assaf, A Schuman International Joint Conferences on Artificial Intelligence (IJCAI), 2019 | 125 | 2019 |
| Modelling and application of condition-based maintenance for a two-component system with stochastic and economic dependencies P Do, R Assaf, P Scarf, B Iung Reliability Engineering & System Safety 182, 86-97, 2019 | 101 | 2019 |
| Mtex-cnn: Multivariate time series explanations for predictions with convolutional neural networks R Assaf, I Giurgiu, F Bagehorn, A Schumann 2019 ieee international conference on data mining (icdm), 952-957, 2019 | 69 | 2019 |
| Touch position detection in electrical tomography tactile sensors through quadratic classifier S Russo, R Assaf, N Carbonaro, A Tognetti IEEE Sensors Journal 19 (2), 474-483, 2018 | 31 | 2018 |
| Wear rate–state interactions within a multi-component system: a study of a gearbox-accelerated life testing platform R Assaf, P Do, S Nefti-Meziani, P Scarf Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2018 | 21 | 2018 |
| Wear rate-state interaction modelling for a multi-component system: Models and an experimental platform R Assaf, P Do, P Scarf, S Nefti-Meziani IFAC-PapersOnLine 49 (28), 232-237, 2016 | 16 | 2016 |
| An anomaly detection and explainability framework using convolutional autoencoders for data storage systems R Assaf, I Giurgiu, J Pfefferle, S Monney, H Pozidis, A Schumann Proceedings of the Twenty-Ninth International Conference on International …, 2021 | 9 | 2021 |
| Diagnosis for systems with multi-component wear interactions R Assaf, P Do, P Scarf, S Nefti-Meziani 2017 IEEE International Conference on Prognostics and Health Management …, 2017 | 9 | 2017 |
| Prognostics and health management for multi-component systems R Assaf PQDT-UK & Ireland, 2018 | 5 | 2018 |
| Towards a practical implementation of EIT-based sensors using artificial neural networks S Russo, R Assaf, S Nefti-Meziani SENSORS, 2017 IEEE, 1-3, 2017 | 5 | 2017 |
| Unsupervised learning for improving fault detection in complex systems R Assaf, S Nefti-Meziani, P Scarf 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM …, 2017 | 5 | 2017 |
| Towards Prognostics and Health Management of Multi-Component Systems with Stochastic Dependence R Assaf, P Do, P Scarf Multicriteria and Optimization Models for Risk, Reliability, and Maintenance …, 2012 | 1 | 2012 |
| Opportunistic maintenance policies for multi-components systems P Do, R Assaf, P Scarf Multicriteria and Optimization Models for Risk, Reliability, and Maintenance …, 2012 | 1 | 2012 |
| Probabilistic feature matching for fast scalable visual prompting T Frick, C Skura, FM Janicki, R Assaf, N Avogaro, D Caraballo-Rivera, ... International Joint Conference on Artificial Intelligence, 2024 | | 2024 |
| AI for Bridge Inspection with IBM Inspecto C Malossi, R Assaf, N Avogaro, A Bartezzaghi, B Ebouky, T Frick, I Giurgiu, ... International Association for Bridge Maintenance and Safety, 2024 | | 2024 |
| Interactive Image Segmentation Guided by Visual Prompting T Frick, C Skura, FM Janicki, R Assaf, N Avogaro, D Caraballo-Rivera, ... IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024 | | 2024 |
| Towards Workflows for the Use of AI Foundation Models in Visual Inspection Applications M Rigotti, D Antognini, R Assaf, K Bakirci, T Frick, I Giurgiu, K Janoušková, ... ce/papers 6 (5), 605-613, 2023 | | 2023 |
| A diagnostics and prognostics framework for multi-component systems with wear interactions: application to a gearbox-platform R Assaf, P Do, P Scarf Pesquisa Operacional 42, e264770, 2022 | | 2022 |
| Wear rate-state interactions within a multi-component R Assaf, P Do, S Nefti-Meziani, PA Scarf Safety 133, 223-236, 2015 | | 2015 |
| CONDITION MONITORING MB THINKlab, MR Assaf, PJB Yang, DL Xu, X Xu | | |
Phil ScarfCardiff UniversityVerified email at cardiff.ac.uk
