Recently, distributed antenna technology based on formation of arrays (FoA) has been proposed in the framework of non-terrestrial network (NTN) integration to provide 5G-like mobile satellite services. To obtain the desired benefits in terms of bitrate...
Innovative technologies powered by Artificial Intelligence have the big potential to support new models of care delivery, disease prevention and quality of life promotion. The ultimate goal is a paradigm shift towards more personalized, accessible,...
In this paper, we present a novel method for the automatic classification of medical images that learns and leverages weak causal signals in the image. Our framework consists of a convolutional neural network backbone and a causality-extractor module...
Causality and eXplainable Artificial Intelligence (XAI) have developed as separate fields in computer science, even though the underlying concepts of causation and explanation share common ancient roots. This is further enforced by the lack of review...
Cine Magnetic Resonance Imaging (MRI) allows for understanding of the heart's function and condition in a non-invasive manner. Undersampling of the k-space is employed to reduce the scan duration, thus increasing patient comfort and reducing the risk...
Cine Magnetic Resonance Imaging (MRI) allows for understanding of the heart's function and condition in a non-invasive manner. Undersampling of the k-space is employed to reduce the scan duration, thus increasing patient comfort and reducing the risk...
The lack of annotated medical images limits the performance of deep learning models, which usually need large-scale labelled datasets. Few-shot learning techniques can reduce data scarcity issues and enhance medical image analysis, especially with...
In this paper, we present a novel method for the automatic classification of medical images that learns and leverages weak causal signals in the image. Our framework consists of a convolutional neural network backbone and a causality-extractor module...
We present a novel technique to discover and exploit weak causal signals directly from images via neural networks for classification purposes. This way, we model how the presence of a feature in one part of the image affects the appearance of another...
Authors: Alessia Silvia Ivani, Federica Barontini, Manuel G. Catalano, Giorgio Grioli, Matteo Bianchi and Antonio Bicchi Published in ICORR 2023 Proceedings
Nome Journal: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment Data pubblicazione: June 2023 Autori: Martina Moglioni, A.C. Kraan, A. Berti, P. Carra, P. Cerello, M. Ciocca,...
Nome Journal: Journal of In-strumentation (JINST) Data pubblicazione: 10 January 2023 Autori: M. Moglioni, A.C. Kraan, A. Berti, P. Carra, P. Cerello, M. Ciocca, V. Ferrero, E. Fiorina, E. Mazzoni, M. Morrocchi, F. Pennazio, A. Retico, V. Rosso, G....
Abstract. Online testing of computer systems is crucial in contexts such as the safety-critical domain, where the software is usually made of functional code, which is the code implementing the application-specific functionalities, and non-functional...
The number of space missions has seen continuous growth in the last years. Accordingly, satellite communications traffic and onboard spacecraft technologies have also increased. To manage high data flows in high-bandwidth communication protocols the...
Nowadays, General Purpose computing on Graphic Processing Unit (GPGPU) is deeply exploited in many application fields due to its high versatility and energy efficiency. Over the past decade, different solutions have been proposed to implement an...
For many years, General Purpose Computing on Graphic Processing Units has been widely exploited in different fields of application. The hardware architectures enabling this kind of computation are increasingly complex, and their use for on-the-edge...