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CARDELLICCHIO, ANGELO

CARDELLICCHIO, ANGELO  

Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA) Sede Secondaria Bari  

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Titolo Data di pubblicazione Autore(i) File
A Review of Deep Learning-Based Anomaly Detection Strategies in Industry 4.0 Focused on Application Fields, Sensing Equipment, and Algorithms 1-gen-2024 Liso, Adriano; Cardellicchio, Angelo; Patruno, Cosimo; Nitti, Massimiliano; Ardino, Pierfrancesco; Stella, Ettore; Renò, Vito
An integrated virtual system for monitoring operations on the railway 1-gen-2024 Di Summa, M.; Cardellicchio, A.; Mosca, N.; Ferraro, P.; Bianco, V.; Stella, E.
Artificial intelligence in structural health management of existing bridges 1-gen-2024 Di Mucci, V. M.; Cardellicchio, A.; Ruggieri, S.; Nettis, A.; Renò, V.; Uva, G.
Automatic detection of typical defects in reinforced concrete bridges via YOLOv5 1-gen-2024 Ruggieri, S.; Cardellicchio, A.; Nettis, A.; Renò, V.; Uva, G.
Automatic quality control of aluminium parts welds based on 3D data and artificial intelligence 1-gen-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 1-gen-2024 Vadukkal, U. K. V.; Cardellicchio, A.; Mosca, N.; Di Summa, M.; Nitti, M.; Stella, E.; Reno', V.
Enhancing Small Object Detection in the YOLOv8 model: A Comprehensive Analysis of the Optimized Model Head Adaptations 1-gen-2024 Solimani, F.; Cardellicchio, A.; Dimauro, G.; Mininni, A.; Calabritto, M.; Di Biase, R.; Petrozza, A.; Summerer, S.; Cellini, F.; Reno, V.
Optimizing tomato plant phenotyping detection: Boosting YOLOv8 architecture to tackle data complexity 1-gen-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 1-gen-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 1-gen-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 1-gen-2023 Renó, Vito; Cardellicchio, Angelo; Romanjenko, Benjamin Conrad; Guadagno, Carmela Rosaria
Assessing Switch Weld Quality with 3D Sensing and Machine Learning 1-gen-2023 Patruno, C.; Nitti, M.; Cardellicchio, A.; Mosca, N.; Di Summa, M.; Reno', V.
AWANDT: Assessing Welding Anomalies via Non-Destructive Tests 1-gen-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 1-gen-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 1-gen-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 1-gen-2023 Cardellicchio, Angelo; Ruggieri, Sergio; Nettis, Andrea; Renò, Vito; Uva, Giuseppina
Tomato detection in challenging scenarios using YOLO-based single stage detectors 1-gen-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 1-gen-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 1-gen-2022 Ruggieri, S; Calo, M; Cardellicchio, A; Uva, G
Deep Learning Approaches for Image-Based Detection and Classification of Structural Defects in Bridges 1-gen-2022 Cardellicchio A.; Ruggieri S.; Nettis A.; Patruno C.; Uva G.; Reno V.