C. Scarselli, F. Pascarella, G. Nenna and A. Monorchio, “Design and Simulation of a Dual Circularly Polarized Receiving Antenna Array for UHF Band”, 2024 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting...
F. Pascarella, D. Brizi and A. Monorchio, “Design of an L-S-Band Frequency Selective Rasorber for Dual-Band Absorption and In-Band Transmission”, 2024 18th European Conference on Antennas and Propagation (EuCAP), Glasgow, United Kingdom, 2024, pp. 1-4,...
Scarselli, F. Pascarella, C. Ciampalini, G. Nenna and A. Monorchio, "Compact Slot-Patch Antenna with Dual Circular Polarization," 2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI), Portland,...
F. Pascarella, C. Scarselli, G. Novellis, G. Nenna and A. Monorchio, "Genetic Algorithm Based Optimization for Concentric Circular Antenna Array Design," 2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting...
In the human body, skin stretch is intrinsically related to motion execution, providing important proprioceptive cues for movement perception and control, as is the case of human hands and fingers. However, as of today, a quantification of the amount...
This paper introduces an innovative robotic solution to autonomously plan stitching paths for two fabric layers. The developed system is inspired by the conventional manufacturing process and aims at assisting the human effort while ensuring...
F. Pascarella, C. Scarselli, G. Novellis, G. Nenna and A. Monorchio, "Genetic AlgorithmF. Pascarella, C. Scarselli, G. Novellis, G. Nenna and A. Monorchio, "Genetic AlgorithmBased Optimization for Concentric Circular Antenna Array Design," 2023 IEEE...
C. Scarselli, E. Giusti, D. Brizi and A. Monorchio, "A Compact Fabry-Perot Cavity Antenna with Circular Polarization," 2024 18th European Conference on Antennas and Propagation (EuCAP), Glasgow, United Kingdom, 2024, pp. 1-3, doi:...
C. Scarselli, F. Pascarella, C. Ciampalini, G. Nenna and A. Monorchio, "Compact Slot-Patch Antenna with Dual Circular Polarization," 2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI),...
The reuse of exhausted electric vehicle batteries in less demanding second-life applications is a promising solution to reduce waste and address concerns about en vironmental sustainability. Unfortunately, the cells used in second-life batteries show...
This work offers insight into the effectiveness of probabilistic models, specifically those based on ensemble approximations, in predicting adverse side effects following radiotherapy for prostate cancer. We trained a random forest model on radiomic...
C. Sbrana, A. Catania, M. Paliy, S. Strangio, M. Macucci, G. Iannaccone, "Design Criteria of High-Temperature Integrated Circuits Using Standard SOI CMOS Process up to 300°C," in IEEE Access, vol. 12, pp. 57236-57249, 2024, doi:...
Reconstructing a large real environment is a fundamental task to promote eXtended Reality adoption in industrial and entertainment fields. However, the short range of depth cameras, the sparsity of LiDAR sensors, and the huge computational cost of...
A responsible approach to artificial intelligence and machine learning technologies, grounded in sound scientific foundations, technical robustness, rigorous testing and validation, risk-based continuous monitoring and alignment with human values is...
Deep learning models in data-scarce domains, such as medical imaging, often suffer from poor performance due to the challenges of acquiring large amounts of labeled data. Few-shot learning offers a promising solution to this problem. This work proposes...
While deep learning excels in many areas, its application in medicine is hindered by limited data, which restricts model generalizability. Few-shot learning has emerged as a potential solution to this problem. In this work, we leverage the strengths of...
Background and objective: Employing deep learning models in critical domains such as medical imaging poses challenges associated with the limited availability of training data. We present a strategy for improving the performance and generalization...
The limited availability of specialized image databases (particularly in hospitals, where tools vary between providers) makes it difficult to train deep learning models. This paper presents a few-shot learning methodology that uses a pre-trained ResNet...