Oceans preservation and protection have become increasingly relevant topics to tackle climate change. To this end, Autonomous Underwater Vehicles (AUVs) provide a useful means to carry out inspection and monitoring operations in full autonomy. A...
The periodical hull inspection represents a necessary task to ensure the maintenance of a vessel since it allows to counteract decay, check for structural damages, and fight the biofouling phenomenon affecting the navigation efficiency. Typically, this...
Autonomous Underwater Vehicles (AUVs) performing visual surveys aimed at the preservation of marine environments are equipped with optical sensors for image acquisition. In addition, an altitude sensor is usually installed on-board to control the...
Integrating Software-Defined Wide Area Networking (SD-WAN) and Satellite 6G can provide a new architecture offering improved performance and reliability for various applications. SD-WAN provides a flexible and efficient system to manage network traffic...
eXplainable Artificial Intelligence (XAI) has been increasingly applied to interpret Deep Neural Networks (DNN) in medical imaging applications, but a general consensus about the best interpretation strategy is missing. This is also due to the absence...
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...