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Akademický článek

AI-aided holographic flow cytometry for label-free identification of ovarian cancer cells in the presence of unbalanced datasets

Autor: F. Borrelli, J. Behal, A. Cohen, L. Miccio, P. Memmolo, I. Kurelac, A. Capozzoli, C. Curcio, A. Liseno, V. Bianco, N. T. Shaked, P. Ferraro

Publikováno v: APL Bioengineering, Vol 7, Iss 2, Pp 026110-026110-10 (2023)

Liquid biopsy is a valuable emerging alternative to tissue biopsy with great potential in the noninvasive early diagnostics of cancer. Liquid biopsy based on single cell analysis can be a powerful approach to identify circulating tumor cells (CTCs) i

Externí odkaz: https://doaj.org/article/ae1b268386f14748a51d3e691ee97ca1

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Akademický článek

CUDA-Based Particle Swarm Optimization in Reflectarray Antenna Synthesis

Autor: A. Capozzoli, C. Curcio, A. Liseno

Publikováno v: Advanced Electromagnetics, Vol 9, Iss 2 (2020)

We show how reflectarray antenna synthesis can take profit from parallel computing on Graphics Processing Units (GPUs). The presented approach uses an implementation of Particle Swarm Optimization in CUDA language and accelerates the computation of t

Externí odkaz: https://doaj.org/article/d896819a38e44936a5add13a0fe2a84c

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Akademický článek

A Comparison of Fast Marching, Fast Sweeping and Fast Iterative Methods for the Solution of the Eikonal Equation

Autor: A. Capozzoli, C. Curcio, A. Liseno, S. Savarese

Publikováno v: Telfor Journal, Vol 6, Iss 2, Pp 142-147 (2014)

We compare the computational performance of the Fast Marching Method, the Fast Sweeping Method and the Fast Iterative Method to determine a numerical solution to the eikonal equation. We point out how the Fast Iterative Method outperforms the other t

Externí odkaz: https://doaj.org/article/8e8a36c77e7d484fb411b7c81183829a

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Akademický článek

Response to Letter to the Editor Regarding 'Real-World Analysis Affirms the High Persistence and Adherence Observed with Diroximel Fumarate in Patients with Multiple Sclerosis'

Autor: Brittney Lager, Jacob Liseno, Ivan Božin, Sarah M. England, Sai L. Shankar, Jason P. Mendoza, James B. Lewin

Publikováno v: Neurology and Therapy, Vol 12, Iss 6, Pp 2199-2203 (2023)

Externí odkaz: https://doaj.org/article/f752573b25fa4a30838db3262a5c2fdd

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Akademický článek

A Learned-SVD Approach to the Electromagnetic Inverse Source Problem

Autor: Amedeo Capozzoli, Ilaria Catapano, Eliana Cinotti, Claudio Curcio, Giuseppe Esposito, Gianluca Gennarelli, Angelo Liseno, Giovanni Ludeno, Francesco Soldovieri

Publikováno v: Sensors, Vol 24, Iss 14, p 4496 (2024)

We propose an artificial intelligence approach based on deep neural networks to tackle a canonical 2D scalar inverse source problem. The learned singular value decomposition (L-SVD) based on hybrid autoencoding is considered. We compare the reconstru

Externí odkaz: https://doaj.org/article/79f45b99fa8e45aab493270b5b8e1bc7

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Akademický článek

Deep learning for accelerating Radon inversion in single-cells tomographic phase imaging flow cytometry

Autor: Borrelli, Francesca, Behal, Jaromir, Bianco, Vittorio, Capozzoli, Amedeo, Curcio, Claudio, Liseno, Angelo, Miccio, Lisa, Memmolo, Pasquale, Ferraro, Pietro

Publikováno v: In Optics and Lasers in Engineering January 2024 172

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Akademický článek

A Phaseless Near-Field to Far-Field Transformation With Planar Wide-Mesh Scanning Accounting for Planar Probe Positioning Errors

Autor: Florindo Bevilacqua, Amedeo Capozzoli, Claudio Curcio, Francesco D'Agostino, Flaminio Ferrara, Claudio Gennarelli, Rocco Guerriero, Angelo Liseno, Massimo Migliozzi

Publikováno v: IEEE Access, Vol 11, Pp 132735-132749 (2023)

This paper proposes a method to correct severe, but known, probe positioning errors affecting a phaseless Planar Wide-Mesh Scanning (PWMS) Near-Field to Far-Field (NFFF) transformation technique and shows its numerical assessment. The involved techni

Externí odkaz: https://doaj.org/article/e7ef5527352a4d87aa079fce3454fa9a

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