Adriano Mancini

Marche Polytechnic University | Università degli Studi di Ancona · Department of Information Engineering (DII)

In the rapidly evolving field of remote sensing, Deep Learning (DL) techniques have become pivotal in interpreting and processing complex datasets. However, the increasing reliance on these algorithms necessitates a robust ethical framework to evaluate their trustworthiness. This paper introduces a comprehensive ethical framework designed to assess...

Legume seeds are essential for nutrition and play crucial roles in food security, climate change mitigation, biodiversity conservation, and sustainability. Among them, the common bean (Phaseolus vulgaris L.) is the most widely cultivated and vital to the food value chain. Originating in Mesoamerica and independently domesticated there and in the An...

Artificial Intelligence (AI) has revolutionized various sectors, including Cultural Heritage (CH) and Creative Industries (CI), defining novel opportunities and challenges in preserving tangible and intangible human productions. In such a context, Neural Rendering (NR) paradigms play the pivotal role of 3D reconstructing objects or scenes by optimi...

Recent advances in Novel-View Synthesis (NVS) and 3D Generation (3DGen) from 2D images have marked significant progress in various domains. While the Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipelines remain prevalent, their limitations have driven the exploration of Deep Learning (DL)-based methods. Among these, Neural Radiance Fiel...

Structural Health Monitoring (SHM) and early warning systems (EWSs) play a pivotal role in enhancing seismic resilience for both buildings and occupants. This paper introduces a monitoring platform that collects electrical impedance data from scaled concrete beams undergoing load and accelerated degradation tests. Artificial Intelligence (AI) algor...

Despite advancements in computer vision technologies, maritime environments continue to pose significant challenges. Varying weather conditions, dynamic water surfaces, and the presence of both large and small objects hamper object detection and tracking and, more in general, the development of robust AI solutions for maritime industry. Addressing...

Background and objective Accurate IVD segmentation is crucial for diagnosing and treating spinal conditions. Traditional deep learning methods depend on extensive, annotated datasets, which are hard to acquire. This research proposes an intensity-based self-supervised domain adaptation, using unlabeled multi-domain data to reduce reliance on large...

The understanding of how users interact with the virtual cultural heritage could provide digital curators valuable insights into user behaviors, and also improve the overall user experience through the ability to observe and record interactions of virtual visitors. This paper introduces the new User Behavior (UB) tracking algorithm that we develope...

In recent years, the safety and integrity of bridges and critical infrastructure have become a paramount concern for governments and societies worldwide. Traditional inspection methods are often time-consuming, prone to human error, and can be economically taxing. The advent of advanced technologies such as Artificial Intelligence (AI) and blockcha...

In the automotive industry, intelligent monitoring systems for advanced human-vehicle interaction aimed at enhancing the safety of drivers and passengers represent a rapidly growing area of research. Safe driving behavior relies on the driver’s awareness of the road context, enabling them to make appropriate decisions and act consistently in anomal...

The use of Artificial Intelligence in Computer Graphics can be applied to video games to a great extent, from human-computer interaction to character animation. The development of increasingly complex environments and, consequently, ever increasing state-spaces, brought the necessity of new AI approaches. This is why Deep Reinforcement Learning is...

In the ever-evolving landscape of retail, understanding shopper behavior is pivotal for optimizing sales and effectively managing product availability and placement. This study explores the integration of autonomous mobile robots into the shelf inspection process, leveraging advancements in automation, information, and robotics technology. Performi...

Presents corrections to the paper, (Corrections to “On the Integration of Artificial Intelligence and Blockchain Technology: A Perspective About Security”).

Forecasting of water availability has become of increasing interest in recent decades, especially due to growing human pressure and climate change, affecting groundwater resources towards a perceivable depletion. Numerous research papers developed at various spatial scales successfully investigated daily or seasonal groundwater level prediction sta...

In computer graphics, 3D modeling is a fundamental concept. It is the process of creating three-dimensional objects or scenes using specialized software that allows users to create, manipulate and modify geometric shapes to build complex models. This operation requires a huge amount of time to perform and specialised knowledge. Typically, it takes...

In retail environment monitor store shelves is a key factor for retailers and brands to provide the best customer shopping experience and maximize sales. Computer vision and deep learning are well suitable this task and are already used for detection and recognition of products displayed in shelves. Recently, retailers started using autonomous robo...

The trajectories of shopping carts and baskets in a supermarket are an information-rich feature that can help in understanding the retail environment, gives idea about the interactions between objects and the ongoing events. This paper is interested in understanding, improving and personalising shopping experience by clustering the trajectories acq...

Water is a vital yet increasingly endangered resource, that stands on the precipice of depletion and degradation, threatened by pollution, overexploitation, habitat alteration, and the looming spectre of climate change. Growing demand for water from various productive sectors and the escalating shifts in weather patterns are among the primary facto...

The preservation, accessibility, and dissemination of historical artifacts to a wider audience have become increasingly important, and cultural institutions can achieve these goals through the digitization of cultural heritage. In recent years, artificial intelligence (AI) and machine learning (ML) techniques improve the virtualization of cultural...

In recent years, the need for contactless and sustainable systems has become increasingly relevant. The traditional water dispensers, which require contact with the dispenser and often involve single-use plastic cups or bottles, are not only unhygienic but also contribute to environmental pollution. This paper presents a touchless water dispenser s...

Predictive Maintenance (PdM) methods aim to facilitate the scheduling of maintenance work before equipment failure. In this context, detecting early faults in automated teller machines (ATMs) has become increasingly important since these machines are susceptible to various types of unpredictable failures. ATMs track execution status by generating m...

The early detection of handguns and knives from surveillance videos is crucial to enhance people’s safety. Despite the increasing development of Deep Learning (DL) methods for general object detection, weapon detection from surveillance videos still presents open challenges. Among these, the most significant are: (i) the very small size of the weap...

The aim of this paper is to present a monitoring system for the built environment based on electrical impedance sensors, together with the development of an early warning system to support decision-making processes in a seismic context. In particular, preliminary data were collected on mortar specimens embedding stainless-steel electrodes for the p...

Predictive Maintenance (PdM) methods aim to facilitate the scheduling of maintenance work before equipment failure. In this context, detecting early faults in automated teller machines (ATMs) has become increasingly important since these machines are susceptible to various types of unpredictable failures. ATMs track execution status by generating m...

Accurate perception and awareness of the environment surrounding the automobile is a challenge in automotive research. This article presents A3CarScene, a dataset recorded while driving a research vehicle equipped with audio and video sensors on public roads in the Marche Region, Italy. The sensor suite includes eight microphones installed inside a...

Vehicle drivers should be able to react coherently in anomalous circumstances, such as the quick arrival of an emergency vehicle with sirens wailing. This situation requires all regular vehicles to give way or slow down, depending on the road and traffic conditions. In this paper, we address an automatic system that assists the driver in reacting t...

The exploitation of offshore mussel farms is becoming relevant almost everywhere, even though it lags way behind other food sectors that are already supported by mature monitoring, modeling, prediction, and analysis tools. New technologies and sensors could indeed boost this sector and alleviate key challenges facing the aquaculture industry. Howev...

In this paper we present a method of the user behavior (UB) tracking by capturing and measuring user activities through the defined procedural model of the reverse virtualization process, implementing a proof of concept on a real case scenario: the Civic Gallery of Ascoli. In order to define the universal model of such “vice versa” virtual reality...

Background and objectives: The use of deep learning for preterm infant's movement monitoring has the potential to support clinicians in early recognizing motor and behavioural disorders. The development of deep learning algorithms is, however, hampered by the lack of publicly available annotated datasets. Methods: To mitigate the issue, this pap...

The Internet of Things (IoT), Big Data and Machine Learning (ML) may represent the foundations for implementing the concept of intelligent production, smart products, services, and predictive maintenance (PdM). The majority of the state-of-the-art ML approaches for PdM use different condition monitoring data (e.g. vibrations, currents, temperature,...

This study wants to give a contribution to the semi-automatic evaluation of rock mass discontinuities, orientation and spacing, as important parameters used in Engineering. In complex and inaccessible study areas, a traditional geological survey is hard to conduct, therefore, remote sensing techniques have proven to be a very useful tool for discon...

Predictive maintenance on infrastructures is currently a hot topic. Its importance is proportional to the damages resulting from the collapse of the infrastructure. Bridges, dams and tunnels are placed on top on the scale of severity of potential damages due to the fact that they can cause loss of lives. Traditional inspection methods are not objec...

This work proposes a pipeline that aims to recognize the products in a shelf, at the level of the single SKU (Stock Keeping Unit), starting from a photo of that shelf. It is composed of a first neural network that detects the individual products on the shelf and has been trained with the SKU110K dataset and a second network, designed and built with...

During the last decade vessel-position-recording devices, such as the Vessel Monitoring System and the Automatic Identification System, have increasingly given accurate spatial and quantitative information of industrial fisheries. On the other hand, small-scale fisheries (vessels below 12 m) remain untracked and largely unregulated even though they...

Tyre brand, its size, model, age and condition monitoring are critical for many vehicle users. The detection and the recognition of plastic components defects result essential. Image classification has become one of the key applications in image processing and computer vision domain. It has been used in several fields such as medical area and intel...

Diabetic Retinopathy (DR) is the most common and insidious microvascular complication of diabetes, and can progress asymptomatically until a sudden loss of vision occurs. Although DR is prevalent nowadays, its prevention remains challenging. The multiple aim of this study was to predict the the risk of developing DR as diabetic complication (task 1...

During the last decade accurate spatial and quantitative information of industrial fisheries have been increasingly given using tracking technologies and machine learning analytical algorithms. However, in most small-scale fisheries, lack of spatial data has been a recurrent bottleneck as Vessel Monitoring System and Automatic Identification System...

Nowadays, video surveillance has a crucial role. Analyzing surveillance videos is, however, a time consuming and tiresome procedure. In the last years, artificial intelligence paved the way for automatic and accurate surveillance-video analysis. In parallel to the development of artificial-intelligence methodologies, edge computing is becoming an a...

Sentiment analysis on social media such as Twitter is a challenging task given the data characteristics such as the length, spelling errors, abbreviations, and special characters. Social media sentiment analysis is also a fundamental issue with many applications. With particular regard of the tourism sector, where the characterization of fluxes is...

Maritime traffic and fishing activities have accelerated considerably over the last decade, with a consequent impact on the environment and marine resources. Meanwhile, a growing number of ship-reporting technologies and remote-sensing systems are generating an overwhelming amount of spatio-temporal and geographically distributed data related to la...

Detecting and tracking people is a challenging task in a persistent crowded environment as retail, airport or station, for human behaviour analysis of security purposes. Especially during the global spread of SARS-CoV-2 virus that has become part of everyday life in every country, it is important to be able to manage the flows inside and outside bu...

Nowadays Human Pose Estimation (HPE) represents one of the main research themes in the field of computer vision. Despite innovative methods and solutions introduced for frame processing algorithms, the use of standard frame-based cameras still has several drawbacks such as data redundancy and fixed frame-rate. The use of event-based cameras guarant...

Objective Decision support systems (DSS) have been developed and promoted for their potential to improve quality of health care. However, there is a lack of common clinical strategy and a poor management of clinical resources and erroneous implementation of preventive medicine. Methods To overcome this problem, this work proposed an integrated syst...

In retail environments, understanding how shoppers move about in a store’s spaces and interact with products is very valuable. While the retail environment has several favourable characteristics that support computer vision, such as reasonable lighting, the large number and diversity of products sold, as well as the potential ambiguity of shoppers’...

The research project named "CREATEFORUAS" aims at enhancing "trustable" flight autonomy for small Unmanned Aircraft Systems (UAS), by tackling different enabling technologies. The paper briefly describes the main research areas of the project which are relevant to vision-based environment understanding, sense and avoid, robust control, and multi-UA...

In the last decades, Computer Engineering has shown an impressive development and has become a pervasive protagonist in daily life and scientific research. Databases and Artificial Intelligence represent two of the major players in this development. Today, they are quickly converging towards a new, much more sophisticated and inclusive, paradigm, n...

Improving the availability of products in a store in order to avoid the OOS (out-of-stock) problem is a crucial topic nowadays. The reduction of OOS events leads to a series of consequences, including, an increase in customer satisfaction and loyalty to the store and brand, the production of positive advertising with a consequent growth in sales, a...

In retail field, customer culture is shifting towards in-store researching, and retailers need to re-evaluate their location services to better assist customer. In-store mapping help retailers learn how their employees are interacting and it satisfies user intent to search for products, something that is often ignored by retailers especially for th...

The Comet Assay is a well-known procedure employed to investigate the DNA damage and can be applied to several research areas such as environmental, medical and health sciences. User dependency and computation time effort represent some of the major drawbacks of the Comet Assay. Starting from this motivation, we applied a Machine Learning (ML) tool...

One of the most challenging problems in precision agriculture is to correctly identify and separate crops from the soil. Current precision farming algorithms based on artificially intelligent networks use multi-spectral or hyper-spectral data to derive radiometric indices that guide the operational management of agricultural complexes. Deep learnin...

In the engineering practice, it frequently occurs that designers, final or intermediate users have to roughly estimate some basic performance or specification data on the basis of input data available at the moment, which can be time-consuming. There is the need for a tool that will fill the missing gap in the optimization problems in engineering d...

Today, e-health has entered the everyday work flow in the form of a variety of healthcare providers. General practitioners (GPs) are the largest category in the public sanitary service, with about 60,000 GPs throughout Italy. Here, we present the Nu.Sa. project, operating in Italy, which has established one of the first GP healthcare information sy...

The acceleration of Digital Agriculture is evident through the increased adoption of digital technologies on farms including smart machines, sensors and cloud computing. In this paper we present the preliminary results of the research project funded by Università Politecnica delle Marche in 2018 “PFRLab: Setting of a precision farming robotic labor...

According to the CEMA, Agriculture 4.0 paves the way for the next evolution of farming consisting of unmanned operations and autonomous decision systems while Agriculture 5.0 will be based around robotics and (some form of) artificial intelligence. It is clear how Agriculture is experimenting a Copernican Revolution where multidisciplinarity is the...

Autonomous systems for monitoring and surveying are increasingly used in retail stores, since they improve the overall performance of the store and reduce the manpower cost. Moreover, an automated system improves the accuracy of collected data by avoiding human-related factors. This paper presents ROCKy, a mobile robot for data collection and surve...

BACKGROUND Sharing General-Practitioners' (GPs) health data has been widely pointed out to be crucial in improving care delivery and achieving a more efficient use of National Health Service (NHS) resources. OBJECTIVE The aim of this paper is to present a Service Oriented Architecture (SOA), called Nu.Sa., that fosters the digitalization, storage...

Understanding shopper behaviour is one of the keys to success for retailers. In particular, it is necessary that managers know which retail attributes are important to which shoppers and their main goal is to improve the consumer shopping experience. In this work, we present sCREEN (Consumer REtail ExperieNce), an intelligent mechatronic system for...

The appeal of energy harvesting systems lies in the possibility of capturing free energy that would be dissipated and is therefore obtainable without costs. Today, advanced techniques and devices exist for capturing from the environment, storing, and managing quotas of natural energy, which are made available in the form of electrical energy. At th...

The development of “intelligent” floors is a growing interest, but often the ensuing solutions involve high production costs as well as complicated installation and management. Aim of this paper is to propose a novel smart floor that makes use of an energy harvesting system in order to allow people localization and to track their movements in an in...

Three-dimensional reconstruction is a very important technique of Computer Vision that produces a three-dimensional (3D) model of a real scene. For this purpose, we use Photometric Stereo that allows you to shape estimation from several images under different lighting conditions. In the last few years, this technology has been used in many areas bo...