| Machine-learning based vulnerability analysis of existing buildings S Ruggieri, A Cardellicchio, V Leggieri, G Uva Automation in Construction 132, 103936, 2021 | 115 | 2021 |
| Detection of tomato plant phenotyping traits using YOLOv5-based single stage detectors A Cardellicchio, F Solimani, G Dimauro, A Petrozza, S Summerer, ... Computers and Electronics in Agriculture 207, 107757, 2023 | 90 | 2023 |
| Physical interpretation of machine learning-based recognition of defects for the risk management of existing bridge heritage A Cardellicchio, S Ruggieri, A Nettis, V Renò, G Uva Engineering Failure Analysis 149, 107237, 2023 | 75 | 2023 |
| Analytical-mechanical based framework for seismic overall fragility analysis of existing RC buildings in town compartments S Ruggieri, M Calò, A Cardellicchio, G Uva Bulletin of Earthquake Engineering 20 (15), 8179-8216, 2022 | 65 | 2022 |
| Optimizing tomato plant phenotyping detection: Boosting YOLOv8 architecture to tackle data complexity F Solimani, A Cardellicchio, G Dimauro, A Petrozza, S Summerer, ... Computers and Electronics in Agriculture 218, 108728, 2024 | 42 | 2024 |
| View VULMA: Data set for training a machine-learning tool for a fast vulnerability analysis of existing buildings A Cardellicchio, S Ruggieri, V Leggieri, G Uva Data 7 (1), 4, 2021 | 25 | 2021 |
| Using machine learning approaches to perform defect detection of existing bridges S Ruggieri, A Cardellicchio, A Nettis, V Renò, G Uva Procedia Structural Integrity 44, 2028-2035, 2023 | 19 | 2023 |
| Automatic quality control of aluminium parts welds based on 3D data and artificial intelligence A Cardellicchio, M Nitti, C Patruno, N Mosca, M di Summa, E Stella, ... Journal of Intelligent Manufacturing 35 (4), 1629-1648, 2024 | 18 | 2024 |
| Artificial intelligence in structural health management of existing bridges VM Di Mucci, A Cardellicchio, S Ruggieri, A Nettis, V Renò, G Uva Automation in Construction 167, 105719, 2024 | 17 | 2024 |
| A systematic review of effective hardware and software factors affecting high-throughput plant phenotyping F Solimani, A Cardellicchio, M Nitti, A Lako, G Dimauro, V Renò Information 14 (4), 214, 2023 | 16 | 2023 |
| Long-term monitoring programs to assess environmental pressures on coastal area: Weighted indexes and statistical elaboration as handy tools for decision-makers M Mali, N Ungaro, A Cardellicchio, MM Dell'Anna, G Romanazzi, ... Ecological Indicators 101, 838-850, 2019 | 14 | 2019 |
| On the use of YOLOv5 for detecting common defects on existing RC bridges A Cardellicchio, S Ruggieri, A Nettis, N Mosca, G Uva, V Renò Multimodal Sensing and Artificial Intelligence: Technologies and …, 2023 | 11 | 2023 |
| IoT and CPS applications based on wearable devices. A case study: Monitoring of elderly and infirm patients A Quarto, D Soldo, S Gemmano, R Dario, V Di Lecce, C Guaragnella, ... 2017 IEEE Workshop on Environmental, Energy, and Structural Monitoring …, 2017 | 10 | 2017 |
| A review of deep learning based anomaly detection strategies in Industry 4.0 focused on application fields, sensing equipment and algorithms A Liso, A Cardellicchio, C Patruno, M Nitti, P Ardino, E Stella, V Renò IEEE Access, 2024 | 9 | 2024 |
| Deep learning approaches for image-based detection and classification of structural defects in bridges A Cardellicchio, S Ruggieri, A Nettis, C Patruno, G Uva, V Renò International Conference on Image Analysis and Processing, 269-279, 2022 | 9 | 2022 |
| A machine learning framework to estimate a simple seismic vulnerability index from a photograph: The VULMA project A Cardellicchio, S Ruggieri, V Leggieri, G Uva Procedia Structural Integrity 44, 1956-1963, 2023 | 7 | 2023 |
| Innovative methodology for detecting of possible harmful compounds for wastewater treatment the MAUI project M Blonda, A Calabrese, A Cardellicchio, B Casale, GD Vincenzo, D Lecce, ... 2018 Workshop on Metrology for Industry 4.0 and IoT, 1-6, 2018 | 4 | 2018 |
| Real-time monitoring system for urban wastewater V Di Lecce, D Petruzzelli, C Guaragnella, A Cardellicchio, G Dentamaro, ... 2017 IEEE Workshop on Environmental, Energy, and Structural Monitoring …, 2017 | 4 | 2017 |
| Patch-based probabilistic identification of plant roots using convolutional neural networks A Cardellicchio, F Solimani, G Dimauro, S Summerer, V Renò Pattern Recognition Letters 183, 125-132, 2024 | 3 | 2024 |
| Using transfer learning technique to define seismic vulnerability of existing buildings through mechanical models S Ruggieri, A Cardellicchio, G Uva Procedia Structural Integrity 44, 1964-1971, 2023 | 3 | 2023 |
Vito RenòConsiglio Nazionale delle Ricerche (CNR)Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα cnr.it