| Automatic autonomous vision-based power line inspection: A review of current status and the potential role of deep learning R Jenssen, D Roverso International Journal of Electrical Power & Energy Systems 99, 107-120, 2018 | 433 | 2018 |
| Intelligent monitoring and inspection of power line components powered by UAVs and deep learning R Jenssen, D Roverso IEEE Power and energy technology systems journal 6 (1), 11-21, 2019 | 161 | 2019 |
| A methodology for security classification applied to smart grid infrastructures M Shrestha, C Johansen, J Noll, D Roverso International Journal of Critical Infrastructure Protection 28, 100342, 2020 | 76 | 2020 |
| Plant diagnostics by transient classification: The aladdin approach D Roverso International Journal of Intelligent Systems 17 (8), 767-790, 2002 | 76 | 2002 |
| Multivariate temporal classification by windowed wavelet decomposition and recurrent neural networks D Roverso 3rd ANS international topical meeting on nuclear plant instrumentation …, 2000 | 67 | 2000 |
| Soft computing tools for transient classification D Roverso Information Sciences 127 (3-4), 137-156, 2000 | 58 | 2000 |
| LS-Net: Fast single-shot line-segment detector VN Nguyen, R Jenssen, D Roverso Machine Vision and Applications 32 (1), 12, 2021 | 57 | 2021 |
| Sen: A novel feature normalization dissimilarity measure for prototypical few-shot learning networks VN Nguyen, S Løkse, K Wickstrøm, M Kampffmeyer, D Roverso, ... Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 37 | 2020 |
| An extended classifiability index for feature selection in nuclear transients E Zio, P Baraldi, D Roverso Annals of Nuclear Energy 32 (15), 1632-1649, 2005 | 37 | 2005 |
| Technical condition assessment and remaining useful life estimation of choke valves subject to erosion BH Nystad, G Gola, JE Hulsund, D Roverso Annual conference of the PHM Society 2 (1), 2010 | 36 | 2010 |
| Fault diagnosis with the aladdin transient classifier D Roverso System Diagnosis and Prognosis: Security and Condition Monitoring Issues III …, 2003 | 35 | 2003 |
| A randomized model ensemble approach for reconstructing signals from faulty sensors P Baraldi, G Gola, E Zio, D Roverso, M Hoffmann Expert Systems with Applications 38 (8), 9211-9224, 2011 | 32 | 2011 |
| Ensemble methods for process monitoring in oil and gas industry operations D Sui, R Nybø, G Gola, D Roverso, M Hoffmann Journal of Natural Gas Science and Engineering 3 (6), 748-753, 2011 | 31 | 2011 |
| Solutions for plant-wide on-line calibration monitoring D Roverso, M Hoffmann, E Zio, P Baraldi, G Gola ESREL 2007, European Safety and Reliability Conference, 827-832, 2007 | 24 | 2007 |
| Abstracting background knowledge for concept learning A Giordana, D Roverso, L Saitta Machine Learning—EWSL-91: European Working Session on Learning Porto …, 1991 | 24 | 1991 |
| Genetic algorithms for signal grouping in sensor validation: a comparison of the filter and wrapper approaches P Baraldi, E Zio, G Gola, D Roverso, M Hoffmann Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2008 | 19 | 2008 |
| Integrating cross-correlation techniques and neural networks for feedwater flow measurement D Ruan, D Roverso, PF Fantoni, JI Sanabrias, JA Carrasco, L Fernandez Progress in Nuclear Energy 43 (1-4), 267-274, 2003 | 18 | 2003 |
| Abstracting concepts with inverse resolution A Giordana, L Saitta, D Roverso Machine Learning Proceedings 1991, 142-146, 1991 | 18 | 1991 |
| Neural ensembles for event identification D Roverso IFAC Proceedings Volumes 33 (11), 469-474, 2000 | 17 | 2000 |
| Two novel procedures for aggregating randomized model ensemble outcomes for robust signal reconstruction in nuclear power plants monitoring systems P Baraldi, E Zio, G Gola, D Roverso, M Hoffmann Annals of Nuclear Energy 38 (2-3), 212-220, 2011 | 16 | 2011 |
