Selenia Ghio

Selenia Ghio

Researcher

0500801556
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Selenia Ghio (born in 1991) received her Bachelor’s degree (2012) and Master’s degree (2015, with honors) in Telecommunications Engineering from the University of Pisa. In 2019, she completed the Ph.D. in Information Engineering at the University of Pisa. She is currently a permanent researcher at the National Laboratory of Radar and Surveillance Systems (RaSS) of CNIT. Her main research interests are in the field of radar signal processing, space situational awareness (SSA), objects’ feature extraction for identification, time-frequency analysis, deep neural networks for target classification, and 3D radar imaging. During her Ph.D., she spent 6 months as a guest researcher at ESA/ESOC (Darmstadt, Germany) collaborating with the space debris team. She has participated in several projects funded by Italian ministries (Ministry of Defense, Ministry of Economic Development, etc.) and European organizations (European Defence Agency (EDA), European Commission). She is a co-author of more than 30 articles and co-editor of the Special Issue “Explainable Artificial Intelligence (XAI) in Radar Imaging: Recent Advances and Future Directions” in the MDPI journal. In 2018, she was awarded the Amelia Earhart Prize.

Publications

2024

Lupidi, A. Giusti, E. Tomei, S. Ghio, S. Martorella, M.

Target Recognition by Means of 3D ISAR Images Conference

2024.

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2023

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

Three-Dimensional Polarimetric InISAR Imaging of Non-Cooperative Targets Journal Article

In: IEEE Transactions on Computational Imaging, vol. 9, pp. 210-223, 2023, (3D-ISAR).

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

Drone-based 3DInISAR: Experimental Results Conference

vol. 2023-May, 2023, (RING).

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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, (3D-ISAR).

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Pui, Chow Yii Ghio, Selenia Ng, Brian Giusti, Elisa Rosenberg, Luke

Robust 3D ISAR Ship Classification Conference

vol. 2023-May, 2023, (RING).

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

Explainability In Hyperspectral Image Classification: A Study of Xai Through the Shap Algorithm Conference

2023.

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Uysal, F. Dorp, P. V. Serrano, A. Kobsa, A. Ghio, S. Kintz, A. Bassa, C. Garrington, S. Cuenca, M. C. Otten, M. Hogan, G. Welch, S. Morrison, R. L. Harrison, P. Wrigley, N. Martorella, M. Usoff, J.

Large Baseline Bistatic Radar Imaging for Space Domain Awareness Conference

2023.

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Serrano, A. Kobsa, A. Uysal, F. Cerutti-Maori, D. Ghio, S. Kintz, A. Morrison, R. L. Jr. Welch, S. van Dorp, P. Hogan, G. Garrington, S. Bassa, C. Saunders, C. Martorella, M. Cuenca, M. Caro Lowe, I.

Long baseline bistatic radar imaging of tumbling space objects for enhancing space domain awareness Journal Article

In: IET Radar, Sonar and Navigation, 2023.

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

Credible Recognition of Radar Images: Interpretability Metric and Classification Score Conference

vol. 2023-July, 2023.

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2022

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

Extended Openmax Approach for the Classification of Radar Images with a Rejection Option Journal Article

In: IEEE Transactions on Aerospace and Electronic Systems, pp. 1-12, 2022, (cited By 0).

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Martorella, M. Giusti, E. Ghio, S. Samczynski, P. Drozdowicz, J. Baczyk, M. K. Wielgo, M. Stasiak, K. Julczyk, J. Ciesielski, M. Soszka, M. Mularzuk, R. Pizziol, G. Stagliano, D. Lischi, S.

3D Radar Imaging for Non-Cooperative Target Recognition Conference

vol. 2022-September, 2022, (RING).

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

Fully polarimetric multi-aspect 3D InISAR Conference

vol. 2022-September, 2022, (3D-ISAR).

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

Low-cost database-free automatic target classification using 3D-ISAR Conference

vol. 2022-September, 2022, (RING).

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

Proportional Similarity-Based Openmax Classifier for Open Set Recognition in SAR Images Journal Article

In: Remote Sensing, vol. 14, no 18, 2022, (cited By 0).

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

Moving and Stationary Targets Separation in SAR Signal Domain Using Parallel Convolutional Autoencoders with RPCA Loss Conference

2022.

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

Open set recognition in sar images using the openmax approach: Challenges and extension to boost the accuracy and robustness Conference

vol. 2022-July, 2022.

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

Open Set Recognition in Synthetic Aperture Radar Using the Openmax Classifier Conference

2022.

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

Comparative assessment of polarimetric features estimation in fully polarimetric 3D-ISAR imaging system Journal Article

In: IET Conference Proceedings, vol. 2022, no 17, pp. 353-358, 2022, (3D-ISAR).

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2021

Ghio, S. Martorella, M. Staglianò, D. Petri, D. Lischi, S. Massini, R.

Experimental comparison of radon domain approaches for resident space object’s parameter estimation Journal Article

In: Sensors (Switzerland), vol. 21, no 4, pp. 1-13, 2021, (cited By 0).

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

Drone-based 3D interferometric ISAR Imaging Conference

vol. 2021-May, 2021, (RING).

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

CNN for Radial Velocity and Range Components Estimation of Ground Moving Targets in SAR Conference

vol. 2021-May, 2021, (ITS2020).

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Oveis, A. H. Guisti, E. Ghio, S. Martorella, M.

A Survey on the Applications of Convolutional Neural Networks for Synthetic Aperture Radar: Recent Advances Journal Article

In: IEEE Aerospace and Electronic Systems Magazine, 2021, (ITS2020).

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Ghio, S. Martorella, M.

Size estimation of space debris models from their RCS measured in anechoic chamber Conference

2021, (cited By 0).

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

Transfer Learning-Based Fully-Polarimetric Radar Image Classification with a Rejection Option Conference

2021, (ITS2020).

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2020

Ghio, S. Martorella, M.

A comparison of radon domain approaches for resident space object's parameter estimation Conference

vol. 2020-October, 2020, (cited By 0).

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Cataldo, D. Gentile, L. Ghio, S. Giusti, E. Tomei, S. Martorella, M.

Multibistatic Radar for Space Surveillance and Tracking Journal Article

In: IEEE Aerospace and Electronic Systems Magazine, vol. 35, no 8, pp. 14-30, 2020, (cited By 0).

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2019

Ghio, S. Martorella, M.

Inverse Radon transform scaling via spin rate estimation for resident space object size assessment Journal Article

In: IET Radar, Sonar and Navigation, vol. 13, no 6, pp. 900-905, 2019, (cited By 0).

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Ghio, S. Martorella, M. Staglianò, D. Petri, D. Lischi, S. Massini, R.

Practical implementation of the spectrogram-inverse Radon transform based algorithm for resident space objects parameter estimation Journal Article

In: IET Science, Measurement and Technology, vol. 13, no 9, pp. 1254-1259, 2019.

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Ghio, S. Martorella, M. Stagliano, D. Petri, D. Lischi, S. Massini, R.

Time-frequency analysis for feature extraction of rotating resident space objects: An experimental test Conference

2019.

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2018

Ghio, S. Martorella, M.

Multi-bistatic radar for resident space objects feature estimation Conference

vol. 2018-June, 2018, (Cited by: 4).

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2017

S., Martorella M. Ghio

Estimation of Rotating RSO Parameters using Radar Data and Joint Time-Frequency Transforms Conference

2017.

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EMPLOYEES

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