CARDELLICCHIO, ANGELO
CARDELLICCHIO, ANGELO
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA)
A Review of Deep Learning-Based Anomaly Detection Strategies in Industry 4.0 Focused on Application Fields, Sensing Equipment, and Algorithms
2024 Liso, Adriano; Cardellicchio, Angelo; Patruno, Cosimo; Nitti, Massimiliano; Ardino, Pierfrancesco; Stella, Ettore; Renò, Vito
Artificial intelligence in structural health management of existing bridges
2024 Di Mucci, V. M.; Cardellicchio, A.; Ruggieri, S.; Nettis, A.; Renò, V.; Uva, G.
Automatic quality control of aluminium parts welds based on 3D data and artificial intelligence
2024 Cardellicchio, A.; Nitti, M.; Patruno, C.; Mosca, N.; di Summa, M.; Stella, E.; Reno', V
Enhancing Railway Safety: An Unsupervised Approach for Detecting Missing Bolts with Deep Learning and 3D Imaging
2024 Vadukkal, U. K. V.; Cardellicchio, A.; Mosca, N.; Di Summa, M.; Nitti, M.; Stella, E.; Reno', V.
Optimizing tomato plant phenotyping detection: Boosting YOLOv8 architecture to tackle data complexity
2024 Solimani, Firozeh; Cardellicchio, Angelo; Dimauro, Giovanni; Petrozza, Angelo; Summerer, Stephan; Cellini, Francesco; Renò, Vito
Patch-based probabilistic identification of plant roots using convolutional neural networks
2024 Cardellicchio, A.; Solimani, F.; Dimauro, G.; Summerer, S.; Reno', V.
A Systematic Review of Effective Hardware and Software Factors Affecting High-Throughput Plant Phenotyping
2023 Solimani, Firozeh; Cardellicchio, Angelo; Nitti, Massimiliano; Lako, Alfred; Dimauro, Giovanni; Renò, Vito
AI-assisted image analysis and physiological validation for progressive drought detection in a diverse panel of Gossypium hirsutum L
2023 Renó, Vito; Cardellicchio, Angelo; Romanjenko, Benjamin Conrad; Guadagno, Carmela Rosaria
Assessing Switch Weld Quality with 3D Sensing and Machine Learning
2023 Patruno, C.; Nitti, M.; Cardellicchio, A.; Mosca, N.; Di Summa, M.; Reno', V.
AWANDT: Assessing Welding Anomalies via Non-Destructive Tests
2023 Liso, A.; Cardellicchio, A.; Patruno, C.; Nitti, M.; Stella, E.; Reno', V.
Detection of tomato plant phenotyping traits using YOLOv5-based single stage detectors
2023 Cardellicchio, Angelo; Solimani, Firozeh; Dimauro, Giovanni; Petrozza, Angelo; Summerer, Stephan; Cellini, Francesco; Renò, Vito
On the use of YOLOv5 for detecting common defects on existing RC bridges
2023 Cardellicchio, A.; Ruggieri, S.; Nettis, A.; Mosca, N.; Uva, G.; Reno', V.
Physical interpretation of machine learning-based recognition of defects for the risk management of existing bridge heritage
2023 Cardellicchio, Angelo; Ruggieri, Sergio; Nettis, Andrea; Renò, Vito; Uva, Giuseppina
Tomato detection in challenging scenarios using YOLO-based single stage detectors
2023 Cardellicchio, A.; Reno', V.; Devanna, R. P.; Marani, R.; Milella, A.
A machine learning framework to estimate a simple seismic vulnerability index from a photograph: the VULMA project
2022 Cardellicchio, A.; Ruggieri, S.; Leggieri, V.; Uva, G.
Analytical-mechanical based framework for seismic overall fragility analysis of existing RC buildings in town compartments
2022 Ruggieri, S; Calo, M; Cardellicchio, A; Uva, G
Deep Learning Approaches for Image-Based Detection and Classification of Structural Defects in Bridges
2022 Cardellicchio A.; Ruggieri S.; Nettis A.; Patruno C.; Uva G.; Reno V.
Using machine learning approaches to perform defect detection of existing bridges
2022 Ruggieri, S.; Cardellicchio, A.; Nettis, A.; Reno', V.; Uva, G.
Using transfer learning technique to define seismic vulnerability of existing buildings through mechanical models
2022 Ruggieri, S.; Cardellicchio, A.; Uva, G.
View VULMA: Data Set for Training a Machine-Learning Tool for a Fast Vulnerability Analysis of Existing Buildings
2022 Cardellicchio; Angelo;Ruggieri; Sergio;Leggieri; Valeria;Uva; Giuseppina