Pietro Ducange
YOU?
Author Swipe
View article: Leveraging Explainable AI for 3D Geometry-Based Channel Status Prediction in UAV-Assisted Communication Networks
Leveraging Explainable AI for 3D Geometry-Based Channel Status Prediction in UAV-Assisted Communication Networks Open
View article: Leveraging Explainable AI for 3-D Geometry-Based Channel Status Prediction in UAV-Assisted Communication Networks
Leveraging Explainable AI for 3-D Geometry-Based Channel Status Prediction in UAV-Assisted Communication Networks Open
Accurate prediction of receiver state is vital for optimizing network performance in urban settings, where rapid spatial variations in channel conditions pose significant challenges to communication quality. This paper presents a Machine L…
View article: Nets4Learning: A Web Platform for Designing and Testing ANN/DNN Models
Nets4Learning: A Web Platform for Designing and Testing ANN/DNN Models Open
Nowadays, any research discipline is interested in tackling its problems with artificial intelligence and, therefore, is demanding knowledge and frameworks with the aim of developing and using intelligent methods. Within this scenario, neu…
View article: Federated Learning of XAI Models in Healthcare: A Case Study on Parkinson’s Disease
Federated Learning of XAI Models in Healthcare: A Case Study on Parkinson’s Disease Open
Artificial intelligence (AI) systems are increasingly used in healthcare applications, although some challenges have not been completely overcome to make them fully trustworthy and compliant with modern regulations and societal needs. Firs…
View article: Increasing trust in AI through privacy preservation and model explainability: Federated Learning of Fuzzy Regression Trees
Increasing trust in AI through privacy preservation and model explainability: Federated Learning of Fuzzy Regression Trees Open
Federated Learning (FL) lets multiple data owners collaborate in training a global model without any violation of data privacy, which is a crucial requirement for enhancing users’ trust in Artificial Intelligence (AI) systems. Despite the …
View article: On Predicting Spare Parts for Field Services by Leveraging Fault Description and Historical Repairing Data
On Predicting Spare Parts for Field Services by Leveraging Fault Description and Historical Repairing Data Open
The traditional process of repairing electrical appliances, including industrial appliances, is activated by a fault report submitted by the owner of the appliance that summarizes the symptoms of the fault. Then, based on their experience …
View article: Enabling federated learning of explainable AI models within beyond-5G/6G networks
Enabling federated learning of explainable AI models within beyond-5G/6G networks Open
View article: Federated Learning of Explainable Artificial Intelligence Models: A Proof-of-Concept for Video-streaming Quality Forecasting in B5G/6G networks
Federated Learning of Explainable Artificial Intelligence Models: A Proof-of-Concept for Video-streaming Quality Forecasting in B5G/6G networks Open
<p>The next generation of mobile networks is poised to rely extensively on Artificial Intelligence (AI) to deliver innovative services. However, it is crucial for AI systems to fulfill key requirements such as trustworthiness, inclus…
View article: OpenFL-XAI: Federated learning of explainable artificial intelligence models in Python
OpenFL-XAI: Federated learning of explainable artificial intelligence models in Python Open
Artificial Intelligence (AI) systems play a significant role in manifold decision-making processes in our daily lives, making trustworthiness of AI more and more crucial for its widespread acceptance. Among others, privacy and explainabili…
View article: Federated TSK Models for Predicting Quality of Experience in B5G/6G Networks
Federated TSK Models for Predicting Quality of Experience in B5G/6G Networks Open
Real-time applications based on streaming data collected from remote devices, such as smartphones and vehicles, are commonly developed using Artificial Intelligence (AI). Such applications must fulfill different requirements: on one hand, …
View article: An Application for Federated Learning of XAI Models in Edge Computing Environments
An Application for Federated Learning of XAI Models in Edge Computing Environments Open
The next generation of wireless networks will feature an increasing number of connected devices which will produce an unprecedented volume of data. Knowledge extraction from decentralized data imposes the exploitation of computing and lear…
View article: Trustworthy AI for Next Generation Networks: the Fed-XAI innovative paradigm from the Hexa-X EU Flagship Project
Trustworthy AI for Next Generation Networks: the Fed-XAI innovative paradigm from the Hexa-X EU Flagship Project Open
This work presents the joint research activities on AI in and for 6G carried out by University of Pisa, Intel Corporation Italia s.p.a. and Telecom Italia s.p.a., within the Hexa-X EU project. Specifically, we focus on Federated Learning o…
View article: Exploiting Simu5G for generating datasets for training and testing AI models for 5G/6G network applications
Exploiting Simu5G for generating datasets for training and testing AI models for 5G/6G network applications Open
View article: Experimental Assessment of Heterogeneous Fuzzy Regression Trees
Experimental Assessment of Heterogeneous Fuzzy Regression Trees Open
Fuzzy Regression Trees (FRTs) are widely acknowledged as highly interpretable ML models, capable of dealing with noise and/or uncertainty thanks to the adoption of fuzziness. The accuracy of FRTs, however, strongly depends on the polynomia…
View article: Data Platform Guidelines and Prototype for Microgrids and Energy Access: Matching Demand Profiles and Socio-Economic Data to Foster Project Development
Data Platform Guidelines and Prototype for Microgrids and Energy Access: Matching Demand Profiles and Socio-Economic Data to Foster Project Development Open
Energy access is a key need for socio-economic growth. Proven to be a key enabler of development and progress, access to electricity has been prioritized by governments using grid extension actions and off-grid solutions, namely microgrids…
View article: The Hexa-X Project Vision on Artificial Intelligence and Machine Learning-Driven Communication and Computation Co-Design for 6G
The Hexa-X Project Vision on Artificial Intelligence and Machine Learning-Driven Communication and Computation Co-Design for 6G Open
This paper provides an overview of the most recent advancements and outcomes of the European 6G flagship project Hexa-X, on the topic of in-network Artificial Intelligence (AI) and Machine Learning (ML). We first present a general introduc…
View article: Fed-XAI: Federated Learning of Explainable Artificial Intelligence Models
Fed-XAI: Federated Learning of Explainable Artificial Intelligence Models Open
The current era is characterized by an increasing pervasiveness of applications and services based on data processing and often built on Artificial Intelligence (AI) and, in particular, Machine Learning (ML) algorithms. In fact, extracting…
View article: Fuzzy Hoeffding Decision Trees for Learning Analytics
Fuzzy Hoeffding Decision Trees for Learning Analytics Open
Pre-Print of the paper that will be published in the CEUR proceedings
View article: Fuzzy Hoeffding Decision Trees for Incremental and Interpretable Predictions of Students' Outcomes
Fuzzy Hoeffding Decision Trees for Incremental and Interpretable Predictions of Students' Outcomes Open
Pre-Print of the Abstract
View article: Hoeffding Regression Trees for Forecasting Quality of Experience in B5G/6G Networks
Hoeffding Regression Trees for Forecasting Quality of Experience in B5G/6G Networks Open
Online data stream analysis is becoming more and more relevant, as the focus of daily life analyses shifts from offline processing to real-time acquisition and modeling of massive data from remote devices. In this paper, we focus our atten…
View article: Federated Learning of Explainable AI Models in 6G Systems: Towards Secure and Automated Vehicle Networking
Federated Learning of Explainable AI Models in 6G Systems: Towards Secure and Automated Vehicle Networking Open
This article presents the concept of federated learning (FL) of eXplainable Artificial Intelligence (XAI) models as an enabling technology in advanced 5G towards 6G systems and discusses its applicability to the automated vehicle networkin…
View article: Pervasive Artificial Intelligence in Next Generation Wireless: The Hexa-X Project Perspective
Pervasive Artificial Intelligence in Next Generation Wireless: The Hexa-X Project Perspective Open
The European 6G flagship project Hexa-X has the objective to conduct exploratory research on the next generation of mobile networks with the intention to connect human, physical and digital worlds with a fabric of technology enablers. With…
View article: Towards Trustworthy AI for QoE prediction in B5G/6G Networks
Towards Trustworthy AI for QoE prediction in B5G/6G Networks Open
The ability to forecast Quality of Experience (QoE) metrics will be crucial in several applications and services offered by the future B5G/6G networks. However, QoE timeseries forecasting has not been adequately investigated so far, mainly…
View article: An Approach to Federated Learning of Explainable Fuzzy Regression Models
An Approach to Federated Learning of Explainable Fuzzy Regression Models Open
Federated Learning (FL) has been proposed as a privacy preserving paradigm for collaboratively training AI models: in an FL scenario data owners learn a shared model by aggregating locally-computed partial models, with no need to share the…
View article: Increasing Accuracy and Explainability in Fuzzy Regression Trees: An Experimental Analysis
Increasing Accuracy and Explainability in Fuzzy Regression Trees: An Experimental Analysis Open
Regression Trees (RTs) have been widely used in the last decades in various domains, also thanks to their inherent explainability. Fuzzy RTs (FRTs) extend RTs by using fuzzy sets and have proven to be particularly suitable for dealing with…
View article: An Intelligent system for the categorization of question time official documents of the Italian Chamber of Deputies
An Intelligent system for the categorization of question time official documents of the Italian Chamber of Deputies Open
In this work, we present an intelligent system for the automatic categorization of political documents, specifically the documents containing the parliamentary questions collected during the weekly Question Times at the Chamber of Deputies…
View article: A News-Based Framework for Uncovering and Tracking City Area Profiles: Assessment in Covid-19 Setting
A News-Based Framework for Uncovering and Tracking City Area Profiles: Assessment in Covid-19 Setting Open
In the last years, there has been an ever-increasing interest in profiling various aspects of city life, especially in the context of smart cities. This interest has become even more relevant recently when we have realized how dramatic eve…
View article: Responsible Artificial Intelligence as a Driver of Innovation in Society and Industry
Responsible Artificial Intelligence as a Driver of Innovation in Society and Industry Open
We describe the most recent research activities of the Artificial Intelligence R&D (AI-RD) group of the Department of Information Engineering of the University of Pisa. The group includes the authors of this contribution (one full professo…
View article: A Federated Fuzzy c-means Clustering Algorithm
A Federated Fuzzy c-means Clustering Algorithm Open
Traditional clustering algorithms require data to be centralized on a single machine or in a datacenter. Due to privacy issues and traffic limitations, in several real applications data cannot be transferred, thus hampering the effectivene…
View article: A Smart System for Personal Protective Equipment Detection in Industrial Environments Based on Deep Learning at the Edge
A Smart System for Personal Protective Equipment Detection in Industrial Environments Based on Deep Learning at the Edge Open
Real-time object detection is currently used to automate various tasks in industrial environments. One of the most important tasks is to improve the safety of workers by monitoring the correct use of Personal Protective Equipment (PPE) in …