Giulio Meucci

Giulio Meucci

Junior Researcher

050 0801558
LinkedIn

Giulio Meucci is a Senior Research collaborator at the CNIT-RaSS National Laboratory since 2021. He holds a bachelor’s degree (2018) and a master’s degree (2021) in Telecommunication Engineering from the University of Pisa, with scores of 103/110 and 109/110, respectively. During his master’s thesis, Giulio focused on finding new approaches to the open set recognition problem in 2D radar applications.

Currently pursuing his PhD at the University of Pisa, Giulio’s research revolves around utilizing machine learning techniques for multi dimensional radar data. He specializes in Automatic Target Recognition (ATR) and radar imaging, with a particular emphasis on employing deep learning methods to enhance ATR performance for electromagnetic images. His work has addressed challenges in open set recognition and incremental learning, resulting in more reliable and adaptable ATR systems in dynamic environments.

Furthermore, Giulio’s contributions extend to 3D-InISAR classification, where he leveraged neural networks to obtain a versatile classifier capable of handling variable input elements for improved target classification in non-cooperative scenarios.

Publications

2023

Oveis, A. H. Giusti, E. Ghio, S. Meucci, G. Martorella, M.

LIME-Assisted Automatic Target Recognition with SAR Images: Toward Incremental Learning and Explainability Journal Article

In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 9175-9192, 2023.

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Oveis, A. H. Giusti, E. Ghio, S. Meucci, G. Martorella, M.

Incremental Learning in Synthetic Aperture Radar Images Using Openmax Algorithm Conference

vol. 2023-May, 2023.

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Meucci, G. Mancuso, F. Giusti, E. Kumar, A. Ghio, S. Martorella, M.

Point Cloud Transformer (PCT) for 3D-InISAR Automatic Target Recognition Conference

vol. 2023-May, 2023.

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2022

Meucci, G. Ghio, S. Giusti, E. Martorella, M.

RADAR TARGET RECOGNITION BASED ON OPEN SET YOLO Journal Article

In: IET Conference Proceedings, vol. 2022, no 17, pp. 377-382, 2022.

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