Francesco Isgrò

University of Naples Federico II | UNINA · Department of Electrical Engineering and Information Technology

The development of continuous river turbidity monitoring systems is essential, since it is a critical water quality metric linked to the presence of organic and inorganic suspended matter. Current monitoring practices are mainly limited by low spatial and temporal resolution, and costs. This results in the huge challenge to provide extensive and ti...

The availability and use of drones, fixed cameras, and smartphones allows the advancement in close range optical remote sensing due to its operability and viability for large-scale implementation. Specifically, RGB cameras are particularly advantageous for low-cost close-range sensing, offering higher spatial resolution at maximum two orders of mag...

Over the past few decades, electroencephalography (EEG) monitoring has become a pivotal tool for diagnosing neurological disorders, particularly for detecting seizures. Epilepsy, one of the most prevalent neurological diseases worldwide, affects approximately the 1 \% of the population. These patients face significant risks, underscoring the need f...

Plastic pollution is a global problem affecting both the riverine and marine environments. However, there is minimal data available to understand plastic transport dynamics, from river upstream to ocean downstream. Quantification of plastic litter has long been a challenge since traditional methods include either manual counting on coastal beaches...

Explainable Artificial Intelligence (XAI) aims to provide insights into the decision-making process of AI models, allowing users to understand their results beyond their decisions. A significant goal of XAI is to improve the performance of AI models by providing explanations for their decision-making processes. However, most XAI literature focuses...

Brain–computer interfaces (BCI) have emerged as a groundbreaking and transformative technology enabling communication between humans and computers through neural systems, primarily electroencephalography (EEG) [...]

Over the last few years, we have seen increasing data generated from non-Euclidean domains, usually represented as graphs with complex relationships. Graph Neural Networks (GNN) have gained a high interest because of their potential in processing graph-structured data. In particular, there is a strong interest in performing convolution on graphs us...

Over the last few years, the availability of an increasing data generated from non-Euclidean domains, which are usually represented as graphs with complex relationships, and Graph Neural Networks (GNN) have gained a high interest because of their potential in processing graph-structured data. In particular, there is a strong interest in performing...

Explainable Artificial Intelligence (XAI) aims to provide insights into the decision-making process of AI models, allowing users to understand their results beyond their decisions. A significant goal of XAI is to improve the performance of AI models by providing explanations for their decision-making processes. However, most XAI literature focuses...

In the context of classification problems, Deep Learning (DL) approaches represent state of art. Many DL approaches are based on variations of standard multi-layer feed-forward neural networks. These are also referred to as deep networks. The basic idea is that each hidden neural layer accomplishes a data transformation which is expected to make th...

Background and objectives: The detection of tumor-infiltrating lymphocytes (TILs) could aid in the development of objective measures of the infiltration grade and can support decision-making in breast cancer (BC). However, manual quantification of TILs in BC histopathological whole slide images (WSI) is currently based on a visual assessment, thus...

The present work concerns side-channel attacks on cryptographic devices protected with the advanced encryption standard. In this regard, the assessment of guessing entropy and the related uncertainty is proposed for machine learning-based attacks based on power measurements. For the first time, the guessing entropy was assessed on the entire key wh...

An interesting case of the well-known Dataset Shift Problem is the classification of Electroencephalo-gram (EEG) signals in the context of Brain-Computer Interface (BCI). The non-stationarity of EEG signals can lead to poor generalisation performance in BCI classification systems used in different sessions, also from the same subject. In this paper...

In the present work, the use of optical cameras for turbidity measurements is tested on the Bode River in Germany, which is one of the best-instrumented catchments in Central Germany with a long-term time series on water quantity and quality. Four trap cameras have been installed on monitored cross-sections with the aim to explore the potential of...

An interesting case of the well-known Dataset Shift Problem is the classification of Electroencephalogram (EEG) signals in the context of Brain-Computer Interface (BCI). The non-stationarity of EEG signals can lead to poor generalisation performance in BCI classification systems used in different sessions, also from the same subject. In this paper,...

In the Machine Learning (ML) literature, a well-known problem is the Dataset Shift problem where, differently from the ML standard hypothesis, the data in the training and test sets can follow different probability distributions, leading ML systems toward poor generalisation performances. This problem is intensely felt in the Brain-Computer Interfa...

Glioblastoma multiforme (GBM) typically exhibits substantial intratumoral heterogeneity at both microscopic and radiological resolution scales. Diffusion Weighted Imaging (DWI) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) are two functional MRI techniques that are commonly employed in clinic for the assessment of GBM tumor c...

A central issue addressed by the rapidly growing research area of eXplainable Artificial Intelligence (XAI) is to provide methods to give explanations for the behaviours of Machine Learning (ML) non-interpretable models after the training. Recently, it is becoming more and more evident that new directions to create better explanations should take i...

The market uptake of Brain-Computer Interface technologies for clinical and non-clinical applications is attracting the scientific world towards the development of daily-life wearable systems. Beyond the use of dry electrodes and wireless technology, reducing the number of channels is crucial to enhance the ergonomics of devices. This paper present...

Nowadays, it is growing interest to make Machine Learning (ML) systems more understandable and trusting to general users. Thus, generating explanations for ML system behaviours that are understandable to human beings is a central scientific and technological issue addressed by the rapidly growing research area of eXplainable Artificial Intelligence...

Over the last few years, we have seen increasing data generated from non-Euclidean domains, which are usually represented as graphs with complex relationships, and Graph Neural Networks (GNN) have gained a high interest because of their potential in processing graph-structured data. In particular, there is a strong interest in exploring the possibi...

This work proposes a novel general framework, in the context of eXplainable Artificial Intelligence (XAI), to construct explanations for the behaviour of Machine Learning (ML) models in terms of middle-level features which represent perceptually salient input parts. One can isolate two different ways to provide explanations in the context of XAI: l...

In neural networks literature, there is a strong interest in identifying and defining activation functions which can improve neural network performance. In recent years there has been a renovated interest of the scientific community in investigating activation functions which can be trained during the learning process, usually referred to as traina...

This work proposes a novel general framework, in the context of eXplainable Artificial Intelligence (XAI), to construct explanations for the behaviour of Machine Learning (ML) models in terms of middle-level features. One can isolate two different ways to provide explanations in the context of XAI: low and middle-level explanations. Middle-level ex...

Machine learning (ML) systems are affected by a pervasive lack of transparency. The eXplainable Artificial Intelligence (XAI) research area addresses this problem and the related issue of explaining the behavior of ML systems in terms that are understandable to human beings. In many explanation of XAI approaches, the output of ML systems are explai...

In the literature, there is a strong interest to identify and define activation functions which can improve neural network performance. In recent years there is a renovated interest of the scientific community in investigating activation functions which can be trained during the learning process, usually referred as trainable, learnable or adaptabl...

Several projects and already-operative observatories aimed at detecting High Energy Cosmic Rays (HECR) are/will be equipped with instruments to monitor the atmosphere. Since cloud presence can affect the night-time indirect measurements of the HECRs and Cherenkov radiation, it is crucial to know the meteorological conditions during the observation...

Providing algorithmic explanations for the decisions of machine learning systems to end users, data protection officers, and other stakeholders in the design, production, commercialisation and use of machine learning systems pipeline is an important and challenging research problem. Much work in this area focuses on image classification, where the...

A pressing research topic is to find ways to explain the decisions of machine learning systems to end users, data officers, and other stakeholders. These explanations must be understandable to human beings. Much work in this field focuses on image classification, as the required explanations can rely on images, therefore making communication relati...

Nell'ambito biomedicale, l'applicazione di tecniche di intelligenza artificiale a dati eterogenei mediante l'integrazione di conoscenza ontologica probabilistica presenta interessanti sfide soprattutto per quel che riguarda la necessità di costruire spiegazioni di quanto ricavato e di rispettare la privatezza dei dati e principi etici condivisi.

Learning automatically the best activation function for the task is an active topic in neural network research. At the moment, despite promising results, it is still difficult to determine a method for learning an activation function that is at the same time theoretically simple and easy to implement. Moreover, most of the methods proposed so far i...

The use of ontological knowledge to improve classification results is a promising line of research. The availability of a probabilistic ontology raises the possibility of combining the probabilities coming from the ontology with the ones produced by a multi-class classifier that detects particular objects in an image. This combination not only prov...

The Japanese Experiment Module-Extreme Universe Space Observatory (JEM-EUSO) telescope will measure ultrahigh-energy cosmic ray properties by detecting the UV fluorescence light generated in the interaction between cosmic rays and the atmosphere. Therefore, information on the state of clouds in the atmosphere is crucial for a proper interpretation...

EUSO-Balloon is a pathfinder mission for the Extreme Universe Space Observatory onboard the Japanese Experiment Module (JEM-EUSO). It was launched on the moonless night of the 25th of August 2014 from Timmins, Canada. The flight ended successfully after maintaining the target altitude of 38 km for five hours. One part of the mission was a 2.5 hour...

EUSO-TA is a ground-based telescope, installed at the Telescope Array (TA) site in Black Rock Mesa, Utah, USA. This is the first detector to use a Fresnel lens based optical system and multi-anode photomultipliers (64 channels per tube, 2304 channels encompassing a 10.6° × 10.6° field of view) for detection of Ultra High Energy Cosmic Rays (UHECR)....

Re-Identification aims to detect the presence of a subject spotted in one video in other videos. Traditional methods use information extracted from single frames like color, clothes, etc. A sequence in time domain of consecutive subject images could contain a greater amount of information compared with a single image of the same subject. Typically,...

Integrating ontological knowledge is a promising research direction to improve automatic image description. In particular, when probabilistic ontologies are available, the corresponding probabilities could be combined with the probabilities produced by a multi-class classifier applied to different parts in an image. This combination not only provid...

JEM-EUSO is a space mission designed to investigate Ultra-High Energy Cosmic Rays and Neutrinos (E>5⋅10¹⁹eV) from the International Space Station (ISS). Looking down from above its wide angle telescope is able to observe their air showers and collect such data from a very wide area. Highly specific trigger algorithms are needed to drastically reduc...

The problem of predictive maintenance is a very crucial one for every technological company. This is particularly true for mobile phones service providers, as mobile phone networks require continuous monitoring. The ability of previewing malfunctions is crucial to reduce maintenance costs and loss of customers. In this paper we describe a prelimina...

We summarize the state of the art of a program of UV observations from space of meteor phenomena, a secondary objective of the JEM-EUSO international collaboration. Our preliminary analysis indicates that JEM-EUSO, taking advantage of its large FOV and good sensitivity, should be able to detect meteors down to absolute magnitude close to 7. This me...

In this paper we present a method to retrieve the Cloud Top Height (CTH), that is a refined version of a stereoscopic method present in literature. It is applied to stereo image pairs obtained by observations of the Meteosat Second Generation (MSG) geostationary satellites in a stereo setup. The performance of the method is tested both as mono band...

In the context of the extraction of the semantic contents important for the effective exploitation of the documents which are now made available by medical information systems, we consider the processing of relations connecting named entities and propose an unsupervised approach to their recognition and labeling. The approach is applied to an Itali...

The annual conference CLIC–it (''Italian Conference on Computational Linguistics'') is an initiative of the ''Italian Association of Computational Linguistics'' (AILC – www.ai-lc.it) which is intended to meet the need for a national and international forum for the promotion and dissemination of high-level original research in the field of Computati...

The Extreme Universe Space Observatory on board the Japanese Experiment Module of the International Space Station, JEM-EUSO, is being designed to search from space ultra-high energy cosmic rays. These are charged particles with energies from a few 1019 eV to beyond 1020 eV, at the very end of the known cosmic ray energy spectrum. JEM-EUSO will also...

Space-based detectors for the study of extreme energy cosmic rays (EECR) are being prepared as a promising new method for detecting highest energy cosmic rays. A pioneering space device – the “tracking ultraviolet set-up” (TUS) – is in the last stage of its construction and testing. The TUS detector will collect preliminary data on EECR in the cond...

The Extreme Universe Space Observatory on the Japanese Experiment Module (JEM-EUSO) on board the International Space Station (ISS) is the first space-based mission worldwide in the field of Ultra High-Energy Cosmic Rays (UHECR). For UHECR experiments, the atmosphere is not only the showering calorimeter for the primary cosmic rays, it is an essenti...

Cloud parameters such as the Cloud Top Height (CTH), Cloud Top Temperature (CTT), emissivity, particle size and optical depth have always been matter of interest for the atmospheric community. Particularly the CTH provides information leading to better understand the cloud radiative effects. Although there are many meteorological satellites providi...

This paper presents a face recognition algorithm based on the matching of local features extracted from face images, namely SIFT. Some of the earlier approaches based on SIFT matching are sensitive to registration errors and usually rely on a very good initial alignment and illumination of the faces to be recognised. The method is based on a new im...

EUSO-Balloon is a pathfinder for JEM-EUSO, the Extreme Universe Space Observatory which is to be hosted on-board the International Space Station. As JEM-EUSO is designed to observe Ultra-High Energy Cosmic Rays (UHECR)-induced Extensive Air Showers (EAS) by detecting their ultraviolet light tracks “from above”, EUSO-Balloon is a nadir-pointing UV t...

Ultra high energy photons and neutrinos are carriers of very important astrophysical information. They may be produced at the sites of cosmic ray acceleration or during the propagation of the cosmic rays in the intergalactic medium. In contrast to charged cosmic rays, photon and neutrino arrival directions point to the production site because they...

Mounted on the International Space Station(ISS), the Extreme Universe Space Observatory, on-board the Japanese Experimental Module (JEM-EUSO), relies on the well established fluorescence technique to observe Extensive Air Showers (EAS) developing in the earth’s atmosphere. Focusing on the detection of Ultra High Energy Cosmic Rays (UHECR) in the de...

The main goal of the JEM-EUSO experiment is the study of Ultra High Energy Cosmic Rays (UHECR, 1019−1021e V), but the method which will be used (detection of the secondary light emissions induced by cosmic rays in the atmosphere) allows to study other luminous phenomena. The UHECRs will be detected through the measurement of the emission in the ran...

The Extreme Universe Space Observatory (EUSO) on–board the Japanese Experimental Module (JEM) of the International Space Station aims at the detection of ultra high energy cosmic rays from space. The mission consists of a UV telescope which will detect the fluorescence light emitted by cosmic ray showers in the atmosphere. The mission, currently de...

The main telescope of JEM-EUSO will determine Ultra High Energy Cosmic Ray properties by measuring the UV fluorescence light generated in the interaction between the cosmic rays and the atmosphere. Therefore, cloud information is crucial for a proper interpretation of the data. JEM-EUSO will observe the clouds in the field of view of the telescope...

This paper discusses the application of an unsupervised text mining technique for the extraction of information from clinical records in Italian. The approach includes two steps. First of all, a metathesaurus is exploited together with natural language processing tools to extract the domain entities. Then, clustering is applied to explore relations...

Nowadays the measurement of the nuchal translucency thickness is being used as part of routine ultrasound scanning during the end of the first trimester of pregnancy, for the screening of chromosomal defects, as trisomy 21. Currently, the measurement is being performed manually by physicians. The measurement can take a long time for being accomplis...

Nailfold capillary microscopy examination has been used for long time as a non invasive technique for the diagnosis of connective tissue diseases. Computer systems helping the physician during the examination have been developed, but they still require a certain level of manual intervention. A first problem that need yet to be solved is the segment...

An Atmospheric Monitoring System (AMS) is mandatory and a key element of a space-based mission which aims to detect Ultra-High Energy Cosmic Rays (UHECR). JEM-EUSO has a dedicated atmospheric monitoring system that plays a fundamental role in our understanding of the atmospheric conditions in the Field of View (FoV) of the telescope. Our AMS consis...

Contributions of the JEM-EUSO Collaboration to the 32nd International Cosmic Ray Conference, Beijing, August, 2011.