Cosimo Distante

Verified

Cosimo verified their affiliation via an institutional email.

Learn more

Verified

Cosimo verified their affiliation via an institutional email.

Learn more

• Ph.D
• Senior Researcher at Italian National Research Council

The aging global population requires innovative remote monitoring systems to assist doctors and caregivers in assessing the health of elderly patients. Doctors often lack access to continuous behavioral data, making it difficult to detect deviations from normal patterns when elderly patients arrive for a consultation. Without historical insights in...

Anomaly detection in time series is essential for industrial monitoring and environmental sensing, yet distinguishing anomalies from complex patterns remains challenging. Existing methods like the Anomaly Transformer and DCdetector have progressed, but they face limitations such as sensitivity to short-term contexts and inefficiency in noisy, non-s...

Purpose: Wireless capsule endoscopy (WCE) is a non-invasive technology used for diagnosing gastrointestinal abnormalities. A single examination generates ∼55;000 images, making manual review both time-consuming and costly for doctors. Therefore, the development of computer vision-assisted systems is highly desirable to aid in the diagnostic process...

Purpose: Wireless capsule endoscopy (WCE) is a non-invasive technology used for diagnosing gastrointestinal abnormalities. A single examination generates ∼ 55,000 images, making manual review both time-consuming and costly for doctors. Therefore, the development of computer vision-assisted systems is highly desirable to aid in the diagnostic proce...

Despite significant advancements in the automatic classification of skin lesions using artificial intelligence (AI) algorithms, skepticism among physicians persists. This reluctance is primarily due to the lack of transparency and explainability inherent in these models, which hinders their widespread acceptance in clinical settings. The primary ob...

During the process of classifying Hyperspectral Image (HSI), every pixel sample is categorized under a land-cover type. CNN-based techniques for HSI classification have notably advanced the field by their adept feature representation capabilities. However, acquiring deep features remains a challenge for these CNN-based methods. In contrast, transfo...

COVID-19 analysis from medical imaging is an important task that has been intensively studied in the last years due to the spread of the COVID-19 pandemic. In fact, medical imaging has often been used as a complementary or main tool to recognize the infected persons. On the other hand, medical imaging has the ability to provide more details about C...

Colorectal cancer is one of the most lethal cancers because of late diagnosis and challenges in the selection of therapy options. The histopathological diagnosis of colon adenocarcinoma is hindered by poor reproducibility and a lack of standard examination protocols required for appropriate treatment decisions. In the current study, using state-of-...

EREMITE is a low-cost and open multi-sensory system that monitors and digitises our coastal marine ecosystems to understand their state, ecological health and functioning, with the concept of any sensor, anytime, anywhere. It is made of an optical multi-sensing system onboard an autonomous sailboat that perceives and reasons about underwater abioti...

Here, we present a comprehensive holography‐based system designed for detecting microparticles through microscopic holographic projections of water samples. This system is designed for researchers who may be unfamiliar with holographic technology but are engaged in microparticle research, particularly in the field of water analysis. Additionally, o...

Detecting and tracking multiple objects from unmanned aerial vehicle (UAV) videos is an high challenging task in a wide range of practical applications. Almost all traditional trackers meet some issues on UAV images due to camera movements causing view change in a 3D directions. In this work, we propose a Convolutional Neural Network specialized in...

Developing computer-aided approaches for cancer diagnosis and grading is receiving an uprising demand since this could take over intra- and inter-observer inconsistency, speed up the screening process, allow early diagnosis, and improve the accuracy and consistency of the treatment planning processes. The third most common cancer worldwide and the...

Microfiber shedding caused by the washing of synthetic textiles is widely recognized as a major source of environmental microplastic pollution. Such a phenomenon pushed the scientific community to develop ever better methodologies for the detection and the identification of synthetic microfibers dispersed in water involving, mainly because of the m...

Developing computer-aided approaches for cancer diagnosis and grading is currently receiving an increasing demand: this could take over intra- and inter-observer inconsistency, speed up the screening process, increase early diagnosis, and improve the accuracy and consistency of the treatment-planning processes.The third most common cancer worldwide...

In the recent years, hyperspectral imaging (HSI) has gained considerably popularity among computer vision researchers for its potential in solving remote sensing problems, especially in agriculture field. However, HSI classification is a complex task due to the high redundancy of spectral bands, limited training samples, and non-linear relationship...

In the last three years, the world has been facing a global crisis caused by Covid-19 pandemic. Medical imaging has been playing a crucial role in the fighting against this disease and saving the human lives. Indeed, CT-scans has proved their efficiency in diagnosing, detecting, and following-up the Covid-19 infection. In this paper, we propose a n...

The epidemiology of COVID-19 presented major shifts during the pandemic period. Factors such as the most common symptoms and severity of infection, the circulation of different variants, the preparedness of health services, and control efforts based on pharmaceutical and non-pharmaceutical interventions played important roles in the disease inciden...

Since the emergence of the Covid-19 pandemic in late 2019, medical imaging has been widely used to analyze this disease. Indeed, CT-scans of the lungs can help diagnose, detect, and quantify Covid-19 infection. In this paper, we address the segmentation of Covid-19 infection from CT-scans. To improve the performance of the Att-Unet architecture and...

Alzheimer’s disease (AD) is the most common form of dementia. Computer-aided diagnosis (CAD) can help in the early detection of associated cognitive impairment. The aim of this work is to improve the automatic detection of dementia in MRI brain data. For this purpose, we used an established pipeline that includes the registration, slicing, and clas...

In this article, we perform the SARIMA model to regress the curve of daily COVID-19 deaths and the impact of implementing restrictive measures like lockdown. For comparison, we adopt two neighboring Brazilian cities with similar characteristics and decompose the original curve of cases to extract the seasonal curve. Using Fast Fourier Transform, we...

In recent years, estimating beauty of faces has attracted growing interest in the fields of computer vision and machine learning. This is due to the emergence of face beauty datasets (such as SCUT-FBP, SCUT-FBP5500 and KDEF-PT) and the prevalence of deep learning methods in many tasks. The goal of this work is to leverage the advances in Deep Learn...

Strong customer authentication (SCA) is a requirement of the European Union Revised Directive on Payment Services (PSD2) which ensures that electronic payments are performed with multifactor authentication. While increasing the security of electronic payments, the SCA impacted seriously on the shopping carts abandonment: an Italian bank computed th...

Since the appearance of Covid-19 pandemic, in the end of 2019, Medical Imaging has been widely used to analysis this disease. In fact, CT-scans of the Lung can help to diagnosis, detect and quantify Covid-19 infection. In this paper, we address the segmentation of Covid-19 infection from CT-scans. In more details, we propose a CNN-based segmentatio...

Non-invasive solutions (no sensors nor markers) appear the most appealing for assessment of body movements and facial dynamics in order to predict Neurodevelopmental disorders (NDD) even in the first days of life. To this aim, recent advances in machine learning applied could be effectively exploited on visual data framing the children, but they su...

Since the appearance of Covid-19 in late 2019, Covid-19 has become an active research topic for the artificial intelligence (AI) community. One of the most interesting AI topics is Covid-19 analysis of medical imaging. CT-scan imaging is the most informative tool about this disease. This work is part of the 2nd COV19D competition, where two challen...

Technological innovations have resulted in a digital transformation in a variety of fields, including culture and tourism. We propose an innovative and personalized solution to benefit art and cultural heritage in indoor and outdoor environments by combining Internet of Things-enabled technologies and deep learning-based approaches. A recent Convol...

In this work, a study on computer vision techniques for automating rendezvous manoeuvres in space has been carried out. A lightweight algorithm pipeline for achieving the 6 degrees of freedom (DOF) object pose estimation, i.e. relative position and attitude, of a spacecraft in a non-cooperative context using a monocular camera has been studied. In...

Having a reliable tool to predict the actions performed in a video can be very useful for intelligent security systems, for many applications related to robotics and for limiting human interactions with the system. In this work we present an architecture trained to predict the action present in digital video sequences. The proposed architecture con...

Cancer ranks as a leading cause of death and an important barrier to increasing life expectancy in every country of the world. For this reason, there is a great requirement for developing computer-aided approaches for accurate cancer diagnosis and grading that can overcome the problem of intra- and inter-observer inconsistency and thereby improve t...

For years now, The International Skin Imaging Collaboration has been providing datasets of dermoscopic images. Several studies show that dermoscopy provides improved diagnostic accuracy, in comparison to standard photography. Excellent results have been obtained that even exceed human performance. In this paper we broke the state of the art for the...

Galaxies morphology classification is a crucial task for studying their physical properties, formation and evolutionary histories. The large-scale surveys on universe has boosted the need to develop techniques for automated galaxies morphological classification. This paper proposes a system able to classify automatically galaxies according to the H...

In the originally published version of chapter 20, the name of the author Pierluigi Carcagnì contained a spelling mistake. This has been corrected.

Neurodevelopmental disorders (NDD) are impairments of the growth and development of the brain and/or central nervous system. In the light of clinical findings on early diagnosis of NDD and prompted by recent advances in hardware and software technologies, several researchers tried to introduce automatic systems to analyse the baby’s movement, even...

This chapter introduces a thorough discussion about the current tools to estimate the epidemiology of COVID-19 focusing on AI strategies. We present in detail both the traditional methods for pandemics forecasting, namely, the SIR, SEIR, SEIRS, SIRD, and ARIMA and novel data-driven approaches that presented promising results, the LSTM, AE, MAE, CNN...

Since the start of the COVID-19 pandemic many studies investigated the correlation between climate variables such as air quality, humidity and temperature and the lethality of COVID-19 around the world. In this work we investigate the use of climate variables, as additional features to train a data-driven multivariate forecast model to predict the...

COVID-19 infection recognition is a very important step in the fight against the COVID-19 pandemic. In fact, many methods have been used to recognize COVID-19 infection including Reverse Transcription Polymerase Chain Reaction (RT-PCR), X-ray scan, and Computed Tomography scan (CT- scan). In addition to the recognition of the COVID-19 infection, CT...

Since the appearance of the COVID-19 pandemic (at the end of 2019, Wuhan, China), the recognition of COVID-19 with medical imaging has become an active research topic for the machine learning and computer vision community. This paper is based on the results obtained from the 2021 COVID-19 SPGC challenge, which aims to classify volumetric CT scans i...

Several studies have found a delay in the development of facial emotion recognition and expression in children with an autism spectrum condition (ASC). Several interventions have been designed to help children to fill this gap. Most of them adopt technological devices (i.e., robots, computers, and avatars) as social mediators and reported evidence...

Covid-19 infection recognition is very important step in the fighting against the new pandemic Covid-19. In fact, many methods have been used to recognize the Covid-19 infection including Reverse transcription polymerase chain reaction (RT-PCR), X-ray scan and CT-scan. In addition to the recognition of the Covid-19 infection, CT-scans can provide m...

In recent years, automatic tissue phenotyping has attracted increasing interest in the Digital Pathology (DP) field. For Colorectal Cancer (CRC), tissue phenotyping can diagnose the cancer and differentiate between different cancer grades. The development of Whole Slide Images (WSIs) has provided the required data for creating automatic tissue phen...

The recognition of COVID-19 infection from X-ray images is an emerging field in the learning and computer vision community. Despite the great efforts that have been made in this field since the appearance of COVID-19 (2019), the field still suffers from two drawbacks. First, the number of available X-ray scans labeled as COVID-19-infected is relati...

We propose a way to perform the classification of holographic phase maps using machine learning models in a web application. The system can perform acquisition, processing, reconstruction, segmentation, and classification steps straight from the browser.

Baggage travelling on a conveyor belt in the sterile area (the rear collector located after the check-in counters) often gets stuck due to traffic jams, mainly caused by incorrect entries from the check-in counters on the collector belt. Using suitcase appearance captured on the Baggage Handling System (BHS) and airport checkpoints and their re-ide...

Diatoms are among the dominant phytoplankters in marine and freshwater habitats, and important biomarkers of water quality, making their identification and classification one of the current challenges for environmental monitoring. To date, taxonomy of the species populating a water column is still conducted by marine biologists on the basis of thei...

The aim of the projects was to develop a software – following the principles of the Facial Action Coding System (Ekman, 1992) – to be applied to a humanoid robot to train children with ASD. The system provided a set of Action Units (AUs) which represented the eye- and mouth-region of the face for basic emotions

Context analysis is a research field that is attracting growing interest in recent years, especially due to the encouraging results carried out by the semantic-based approach. Anyway, semantic strategies entail the use of trackers capable to show robustness to long-term occlusions, viewpoint changes and identity swap that represent the main problem...

The contribution of this paper is twofold. First, a new data driven approach for predicting the Covid-19 pandemic dynamics is introduced. The second contribution consists in reporting and discussing the results that were obtained with this approach for the Brazilian states, with predictions starting as of 4 May 2020. As a preliminary study, we firs...

The automatic detection of eye positions, their temporal consistency, and their mapping into a line of sight in the real world (to find where a person is looking at) is reported in the scientific literature as gaze tracking. This has become a very hot topic in the field of computer vision during the last decades, with a surprising and continuously...

Knowing an accurate passengers attendance estimation on each metro car contributes to the safely coordination and sorting the crowd-passenger in each metro station. In this work we propose a multi-head Convolutional Neural Network (CNN) architecture trained to infer an estimation of passenger attendance in a metro car. The proposed network architec...

Soft biometrics provide information about the individual but without the distinctiveness and permanence able to discriminate between any two individuals. Since the gaze represents one of the most investigated human traits , works evaluating the feasibility of considering it as a possible additional soft biometric trait have been recently appeared i...

This paper has a twofold contribution. The first is a data driven approach for predicting the Covid-19 pandemic dynamics, based on data from more advanced countries. The second is to report and discuss the results obtained with this approach for Brazilian states, as of May 4th, 2020. We start by presenting preliminary results obtained by training a...

Epidemiological figures of the SARS-CoV-2 epidemic in Italy are higher than those observed in China. Our objective was to model the SARS-CoV-2 outbreak progression in Italian regions vs. Lombardy to assess the epidemic’s progression. Our setting was Italy, and especially Lombardy, which is experiencing a heavy burden of SARS-CoV-2 infections. The p...

Background Epidemiological figures of Covid-19 epidemic in Italy are worse than those observed in China. Methods We modeled the Covid-19 outbreak in Italian Regions vs. Lombardy to assess the epidemics progression and predict peaks of new daily infections and total cases by learning from the entire Chinese epidemiological dynamics. We trained an a...

Background Italy and especially the Lombardy region is experiencing a heavy burden of Covid-19 infection. The peak of the epidemics has not yet been reached and it is expected to be delayed in Central and Southern Italian regions compared to Northern ones. We have modeled the Covid-19 outbreak progression in Italian Regions vs. Lombardy. Methods I...

This paper gives an overview of the cutting-edge approaches that perform facial cue analysis in the healthcare area. The document is not limited to global face analysis but it also concentrates on methods related to local cues (e.g., the eyes). A research taxonomy is introduced by dividing the face in its main features: eyes, mouth, muscles, skin,...

Microplastics are a major environmental concern due to their possible impact on water pollution, wildlife and food chain. Reliable, rapid and high‐throughput screening of microplastics from other components of a water sample after sieving and/or digestion is still a highly desirable goal to avoid cumbersome visual analysis by expert users under the...

Achieving clear imaging through fire is a highly pursued goal and various active field-portable devices have been recently proposed to improve the capabilities of existing thermographic cameras. Here we combine an Infrared active imaging sensor and artificial intelligence to obtain automatic detection of people hidden behind flames. We show the suc...

Across three volumes, the Handbook of Image Processing and Computer Vision presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding. The authoritative insights presented within cover all aspects of t...

Across three volumes, the Handbook of Image Processing and Computer Vision presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding. The authoritative insights presented within cover all aspects of t...

Across three volumes, the Handbook of Image Processing and Computer Vision presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding. The authoritative insights presented within cover all aspects of t...

We present and test a prototype of a compact, light in weight, cost effective and field portable off-axis DH microscope based on the concept of the Holographic Microscope Slide.

An effective strategy, that combines Digital Holography with machine learning, for achieving accurate and automatic identification of microplastics in filtered water sample, is proposed, reaching over 99% in classification performance among microplastics and diatoms.

The computational analysis of facial expressions is an emerging research topic that could overcome the limitations of human perception and get quick and objective outcomes in the assessment of neurodevelopmental disorders (e.g., Autism Spectrum Disorders, ASD). Unfortunately, there have been only a few attempts to quantify facial expression product...

Automatic recognition and classification of skin diseases is an area of research that is gaining more and more attention. Unfortunately, most relevant works in the state of the art deal with a binary classification between malignant and non-malignant examples and this limits their use in real contexts where the classification of the specific pathol...