Giuseppe Pirlo

Università degli Studi di Bari Aldo Moro | Università di Bari · Department of Computer Science

Background and objective: Neurodegenerative diseases are the most frequent age-related diseases. This type of disease, if not discovered in the initial stage, will compromise the quality of life of the affected subject. Thus, a timely diagnosis is of paramount importance. One of the most used tasks from neurologists to detect and determine the sev...

The smartphone is an excellent source of data; it is possible to extrapolate smartphone sensor values and, through Machine Learning approaches, perform anomaly detection analysis characterized by human behavior. This work exploits Human Activity Recognition (HAR) models and techniques to identify human activity performed while filling out a questio...

Describing an image scene in Natural Language is a very complex procedure for a machine. Many researchers have used Natural Language Processing approaches. In this paper Machine Learning and Computer Vision models will be illustrated with the purpose of describing a picture in the wild. Action Recognition models, Face Recognition with gender and ag...

Demand for electricity is constantly increasing, and production is facing new constraints due to the current world situation. An alternative to standard energy production methodologies is based on the use of renewable sources; however, these methodologies do not produce energy consistently due to weather factors. This results in a significant commi...

Timely diagnosis plays a crucial role for the treatment of neurodegenerative diseases. In particular, Dementia Identification in early stages is important to help patients have a better quality of life and to help clinicians to find a pathway of treatments to slow the effects. To the aim, a wide set of different handwriting tasks is here considered...

This article shows a system performing re-identification and description of people entering different stores of the same franchise by means of Face Recognition, Gait Analysis, and Soft Biometrics techniques. Additionally, an anomaly detection analysis is conducted to identify suspicious behavioral patterns.It has been tested on an ad-hoc dataset of...

This study presents the Auditory Cortex ResNet (AUCO ResNet), it is a biologically inspired deep neural network especially designed for sound classification and more specifically for Covid-19 recognition from audio tracks of coughs and breaths. Differently from other approaches, it can be trained end-to-end thus optimizing (with gradient descent) a...

The 0-day attack is a cyber-attack based on vulnerabilities that have not yet been published. The detection of anomalous traffic generated by such attacks is vital, as it can represent a critical problem, both in a technical and economic sense, for a smart enterprise as for any system largely dependent on technology. To predict this kind of attack,...

Recognition of malware is critical in cybersecurity as it allows for avoiding execution and the downloading of malware. One of the possible approaches is to analyze the executable’s Application Programming Interface (API) calls, which can be done using tools that work in sandboxes, such as Cuckoo or CAPEv2. This chain of calls can then be used to c...

The following work proposes a benchmark of performances of state of art AI algorithms for the weapons detection. Particularly, it is aimed to test three CNN based models on the task of detecting specific types of weapons. In order to accomplish this goal, four datasets are employed. Additionally, due to the lack of rich amounts of well-structured d...

The generation of encrypted channels between more than two users is complex, as it is necessary to share information about the key of each user. This problem has been partially solved through the secret sharing mechanism that makes it possible to divide a secret among several participants, so that the secret can be reconstructed by a well-defined p...

In this extended version of this paper, an automatic video diagnosis system for dementia classification is presented. Starting from video recordings of patients and control subjects, performing sit-to-stand test, the designed system is capable of extracting relevant patterns for binary discern patients with dementia from healthy subjects. The origi...

This work considers the Internet of Things (IoT) and machine learning (ML) applied to the agricultural sector within a real-working scenario. More specifically, the aim is to punctually forecast two of the most important meteorological parameters (solar radiation and the rainfall) to determine the amount of water needed by a specific plantation und...

Neurodegenerative diseases are incurable diseases where a timely diagnosis plays a key role. For this reason, various techniques of computer aided diagnosis (CAD) have been proposed. In particular handwriting is a well-established diagnosis technique. For this reason, an analysis of state-of-the-art technologies, compared to those which historicall...

This work inspects deep learning architectures and shallow learning techniques to determine whether the image of a fingerprint is real (Live) or not (Fake). It is known that Deep Learning techniques deliver, in general, good accuracies being able to automatically extract relevant patterns, at the same time, it is also known that these algorithms re...

The standards defined by the human-computer interaction discipline highlight the need for renewed interpretation of services for the customer. Indeed the increasing number of original applications based on the progression of technology and the spread of sensors in almost every space (private and public) is the ground of potential benefits for the e...

This paper reviews the recent literature on technologies and methodologies for quantitative human gait analysis in the context of neurodegnerative diseases. The use of technological instruments can be of great support in both clinical diagnosis and severity assessment of these pathologies. In this paper, sensors, features and processing methodologi...

Neurodegenerative disease assessment with handwriting has been shown to be effective. In this exploratory analysis, several features are extracted and tested on different tasks of the novel HAND-UNIBA dataset. Results show what are the most important kinematic features and the most significant tasks for neurodegenerative disease assessment through...

This work exploits Touch Dynamics to recognize affective states of a user while using a mobile device. To the aim, the acquired touch pattern is segmented in swipes, successively a wide set of handcrafted features is computed to characterize the swipe. The affective analysis is obtained through machine learning techniques. Data have been collected...

This chapter investigates the use of the sigma-lognormal model of the Kinematic Theory of rapid human for discriminating parkinsonian handwriting from healthy controls. Sigma-lognormal features are combined with more classic measures thus improving state-of-the-art results.

In this paper, an automatic video diagnosis system for dementia classification is presented. Starting from video recordings of patients and control subjects, performing sit-to-stand test, the designed system is capable of extracting relevant patterns for binary discern patients with dementia from healthy subjects. The proposed system achieves an ac...

The Internet of Things (IoT) paradigm applied to the agriculture field provides a huge amount of data allowing the employment of Artificial Intelligence for multiple tasks. In this work, solar radiation prediction is considered. To the aim, Multi-Layer Perceptron is adopted considering a complete real complex use case and real-time working conditio...

This benchmarking study aims to examine and discuss the current state-of-the-art techniques for in-video violence detection, and also provide benchmarking results as a reference for the future accuracy baseline of violence detection systems. In this paper, the authors review 11 techniques for in-video violence detection. They re-implement five care...

Smart cities work under a more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which have led to the creation of smart enterprises and organizations that depend on advanced technologies. In this Special Issue, 21 selected and peer-reviewed articles contributed in th...

Every day millions of people drive along urban roads and highways featuring driving own behaviors. When considering the highway network, great efforts have been employed to monitoring such large number of users considering traffic code infringements, accidents detection or traffic congestion estimation. Such information are useful to reveal hidden...

This paper presents a preliminary easy to explain and effective framework for supporting dynamic signature analysis in forensic settings. The proposed approach is based on measuring similarities among signatures by applying Dynamic Time Warping on easy to derive dynamic measures. The long term goal of our research is to provide forensic handwriting...

Neurodegenerative diseases are particular diseases whose decline can partially or completely compromise the normal course of life of a human being. In order to increase the quality of patient’s life, a timely diagnosis plays a major role. The analysis of neurodegenerative diseases, and their stage, is also carried out by means of gait analysis. Per...

Vehicular traffic flow prediction for a specific day of the week in a specific time span is valuable information. Local police can use this information to preventively control the traffic in more critical areas and improve the viability by decreasing, also, the number of accidents. In this paper, a novel generative deep learning architecture for ti...

Automatic traffic flow classification is useful to reveal road congestions and accidents. Nowadays, roads and highways are equipped with a huge amount of surveillance cameras, which can be used for real-time vehicle identification, and thus providing traffic flow estimation. This research provides a comparative analysis of state-of-the-art object d...

Diagnosing and monitoring Parkinson’s disease (PD) is a topic of current research in many fields, including AI. The innovative challenge is to develop a low-cost, non-invasive tool to support clinicians at the point of care. In particular, since handwriting difficulties in PD patients are well-known, changes in handwriting have emerged as a powerfu...

Education may play a key role in developing "cognitive reserve" against neurodegenerative dementia. In this work, we investigate for the first time if handwriting dynamics can serve as a quantitative indicator of this reserve. We carried out an exploratory study involving a sample of mild cognitive impairment (MCI) subjects, with high and low educa...

In the present paper, we propose an evolutionary approach to address interoperability issues in multi-device signature verification, based on transformation mappings automatically tuned by a genetic algorithm. These mappings are meant to decrease dissimilarities between signatures acquired through different devices and with different modalities (st...

Touch Dynamics is the behavioral biometric trait that regards how the user interacts with devices equipped with touch displays, the dynamic patterns drawn through the swipe movement can be used to identify the user who is accessing the smartphone. In this paper we investigated whether the same data could be used also to recognize some emotional sta...

Water scarcity is one of the main issues that agriculture must face since an increase is expected not only in developing countries but also in southern Europe with Italy featuring a long-term annual average estimated in 1.909 m³ per inhabitant. To deal with this problem, the EcoLoop project presented in this work proposes an ICT system able to coll...

In this paper, an automatic diagnosis system for neurodegenerative diseases is presented. Starting with an existing neurodegenerative diseases gait dataset, namely the NDDGD dataset, classification and regression algorithms have been trained, with the inter-patient dataset separation scheme (walking patterns used for training and testing, belong to...

Computer aided diagnosis systems can provide non-invasive, low-cost tools to support clinicians. These systems have the potential to assist the diagnosis and monitoring of neurodegenerative disorders, in particular Parkinson's disease (PD). Handwriting plays a special role in the context of PD assessment. In this paper, the discriminating power of...

Handwriting dynamics is relevant to discriminate people affected by neurodegenerative dementia from healthy subjects. This can be possible by administering simple and easy-to-perform handwriting/drawing tasks on digitizing tablets provided with electronic pens. Encouraging results have been recently obtained; however, the research community still l...

Reduced training sets are major problems typically found on the task of offline signature verification. To increase the number of samples, the use of synthetic signatures can be taken into account. In this work, a new method for the generation of synthetic offline signatures by using dynamic and static (real) ones is presented. The synthesis is her...

This paper proposes a novel technique for an automatic detection of dementia based on the Attentional Matrices test (AMT) for selective attention assessment. The original test provides three matrices, of increasing difficulty, and the test taker is asked to mark target digits assigned. In our proposal, AMT was developed on a digitizing tablet, equi...

Artificial intelligence is changing the healthcare industry from many perspectives: diagnosis, treatment, and follow-up. A wide range of techniques has been proposed in the literature. In this special issue, 13 selected and peer-reviewed original research articles contribute to the application of artificial intelligence (AI) approaches in various r...

Il progetto di ricerca industriale e sviluppo sperimentale denominato BESIDE intende applicare tecniche di intelligenza artificiale per l’analisi di pattern motori (Gait Analysis) e comportamentali di individui affetti da malattie neurodegenerative. In particolare, il progetto intende individuare i sensori più idonei e sviluppare un complesso siste...

Multiclass classification in cancer diagnostics, using DNA or Gene Expression Signatures, but also classification of bacteria species fingerprints in MALDI-TOF mass spectrometry data, is challenging because of imbalanced data and the high number of dimensions with respect to the number of instances. In this study, a new oversampling technique calle...

This work presents the practical design of a system that faces the problem of identification and validation of private no-parking road signs. This issue is very important for the public city administrations since many people, after receiving a code that identifies the signal at the entrance of their private car garage as valid, forget to renew the...

On-line signature verification is typically carried out with the use of digitizing tablets specifically designed for the aim. So far, stand-alone systems have been mainly inspected, but the current distributed/cloud scenario and the amount of mobile devices in everyday life is calling for a new challenge. Within this scenario, signatures are acquir...

Machine learning techniques are tailored to build intelligent systems to support clinicians at the point of care. In particular, they can complement standard clinical evaluations for the assessment of early signs and manifestations of Parkinson's disease (PD). Patients suffering from PD typically exhibit impairments of previously learned motor skil...

This work aims to show how to manage heterogeneous information and data coming from real datasets that collect physical, biological, and sensory values. As productive companies—public or private, large or small—need increasing profitability with costs reduction, discovering appropriate ways to exploit data that are continuously recorded and made av...

Handwritten signatures are biometric traits increasingly at the centre of debate by the scientific community. Over the last forty years, the interest in signature studies has grown steadily, having as its main reference in the application of automatic signature verification, as previously published reviews in 1989, 2000 and 2008 bear witness. Ever...

Neurodegenerative diseases, as for instance Alzheimer's Disease (AD) and Parkinson's Disease (PD), affect the peripheral nervous system, where nerve cells send the messages that control muscles in order to allow movements. Sick neurons cannot control muscles properly. Handwriting involves cognitive planning, coordination and execution abilities. Si...

Neurodegenerative diseases (NDs) affect millions of people worldwide, with Alzheimer's and Parkinson's being the most common ones, and it is expected that their incidence will dramatically increase in the next few decades. Unfortunately, these diseases cannot be cured, but an early diagnosis can help to better manage their symptoms and their evolut...

The relation between handwriting and Alzheimer's Disease (AD) as well as Parkinson's Disease (PD) has been studied so far. However it is just in the last 5-6 years that Computer Aided Diagnosis system have been considered. Of course the current stage of development is still in the direction of healthy vs. non healthy classification. This work inten...

This paper presents a new convolutional neural network architecture for heartbeat classification. The architecture, that uses a reduced number of layers, with respect to other CNN used for heartbeat classification, is able to achieve high accuracy in heartbeat classification following the AAMI recommendations. In particular, using the well-known an...

The widespread availability of hand-held devices like tablets, phablets and smart phones, along with their new handwriting digitizing and their increased computing powers, enable these to process the graphomotor dimension and the lognormal trends of human handwriting. By exploiting such capacity, it becomes possible to extend these mobile devices i...

Kinematic features of the handwriting process are promising for discriminating patients probably affected by neurodegenerative disorders from healthy controls and potentially for identifying the stage of the illness. Many tasks have been proposed and tested, however the scientific community still lacks a complete protocol able to collect different...

Degenerative nerve diseases affect many of your body's activities , such as balance, movement, talking, breathing, and heart function. These disease cannot be cured, nonetheless an early diagnosis can help to better manage the symptoms and the evolution of these diseases. Since handwriting involves several cognitive abilities, clinicians started to...

The papers in this special section focus on handwriting and drawing processes for user-centered systems. The papers provide a wide and updated overview of the frontier of research in the field of humancentered systems based on drawing and handwriting processing. Through the papers, some of the most relevant directions of further research are highli...

In recent years, with the widespread of internet and digitized processing of multi–script documents worldwide, script identification techniques have become more important in the pattern recognition field. Script identification concerns methods for identifying different scripts in multi-lingual, multi-script documents. This paper presents a comprehe...

This chapter introduces the problem of non-modular operations in the Residue Number System (RNS) and presents some recent approaches for their effective implementation. The approaches are based on specific functions defined from the RNS to the Integers that show mathematical properties useful to support the implementation of non-modular operations,...

This paper presents a new and straightforward system for bearing fault detection. The system computes the stability of two vibration signals by using the direct matching points (DMP) of an elastic and non-linear align function. It is able to find discriminant properties in the stability of fault-free and faulty bearing vibration signals from the ea...

This book has the primary goal of presenting and discussing some recent advances and ongoing developments in the Handwritten Text Recognition (HTR) field, resulting from works done on different HTR-related topics for the achievement of more accurate and efficient recognition systems. Nowadays, there is an enormous worldwide interest in HTR systems,...