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2021 Conference article Open Access OPEN

Learning topology: bridging computational topology and machine learning
Moroni D., Pascali M. A.
Topology is a classical branch of mathematics, born essentially from Euler's studies in the XVII century, which deals with the abstract notion of shape and geometry. Last decades were characterised by a renewed interest in topology and topology-based tools, due to the birth of computational topology and Topological Data Analysis (TDA). A large and novel family of methods and algorithms computing topological features and descriptors (e.g. persistent homology) have proved to be effective tools for the analysis of graphs, 3d objects, 2D images, and even heterogeneous datasets. This survey is intended to be a concise but complete compendium that, offering the essential basic references, allows you to orient yourself among the recent advances in TDA and its applications, with an eye to those related to machine learning and deep learning.Source: ICPR 2021: Pattern Recognition. ICPR International Workshops and Challenges, Milan, Italy - Fully virtual event, 11/01/2021
DOI: 10.1007/978-3-030-68821-9_20

See at: link.springer.com Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | link.springer.com Restricted


2021 Report Open Access OPEN

SI-Lab Annual Research Report 2020
Leone G. R., Righi M., Carboni A., Caudai C., Colantonio S., Kuruoglu E. E., Leporini B., Magrini M., Paradisi P., Pascali M. A., Pieri G., Reggiannini M., Salerno E., Scozzari A., Tonazzini A., Fusco G., Galesi G., Martinelli M., Pardini F., Tampucci M., Buongiorno R., Bruno A., Germanese D., Matarese F., Coscetti S., Coltelli P., Jalil B., Benassi A., Bertini G., Salvetti O., Moroni D.
The Signal & Images Laboratory (http://si.isti.cnr.it/) is an interdisciplinary research group in computer vision, signal analysis, smart vision systems and multimedia data understanding. It is part of the Institute for Information Science and Technologies of the National Research Council of Italy. This report accounts for the research activities of the Signal and Images Laboratory of the Institute of Information Science and Technologies during the year 2020.Source: ISTI Technical Report, ISTI-2021-TR/009, pp.1–38, 2021
DOI: 10.32079/isti-tr-2021/009

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2021 Journal article Open Access OPEN

Learning topology: bridging computational topology and machine learning
Moroni D., Pascali M. A.
Topology is a classical branch of mathematics, born essentially from Euler's studies in the XVII century, which deals with the abstract notion of shape and geometry. Last decades were characterized by a renewed interest in topology and topology-based tools, due to the birth of computational topology and topological data analysis (TDA). A large and novel family of methods and algorithms computing topological features and descriptors (e.g., persistent homology) have proved to be effective tools for the analysis of graphs, 3D objects, 2D images, and even heterogeneous datasets. This survey is intended to be a concise but complete compendium that, offering the essential basic references, allows you to orient yourself among the recent advances in TDA and its applications, with an eye to those related to machine learning and deep learning.Source: Pattern recognition and image analysis 31 (2021): 443–453. doi:10.1134/S1054661821030184
DOI: 10.1134/s1054661821030184

See at: ISTI Repository Open Access | CNR ExploRA Restricted


2020 Journal article Open Access OPEN

Monitoring ancient buildings: real deployment of an IoT system enhanced by UAVs and virtual reality
Bacco M., Barsocchi P., Cassarà P., Germanese D., Gotta A., Leone G. R., Moroni D., Pascali M. A., Tampucci M.
The historical buildings of a nation are the tangible signs of its history and culture. Their preservation deserves considerable attention, being of primary importance from a historical, cultural, and economic point of view. Having a scalable and reliable monitoring system plays an important role in the Structural Health Monitoring (SHM): therefore, this paper proposes an Internet Of Things (IoT) architecture for a remote monitoring system that is able to integrate, through the Virtual Reality (VR) paradigm, the environmental and mechanical data acquired by a wireless sensor network set on three ancient buildings with the images and context information acquired by an Unmanned Aerial Vehicle (UAV). Moreover, the information provided by the UAV allows to promptly inspect the critical structural damage, such as the patterns of cracks in the structural components of the building being monitored. Our approach opens new scenarios to support SHM activities, because an operator can interact with real-time data retrieved from a Wireless Sensor Network (WSN) by means of the VR environment.Source: IEEE access (2020). doi:10.1109/ACCESS.2020.2980359
DOI: 10.1109/access.2020.2980359

See at: IEEE Access Open Access | IEEE Access Open Access | ieeexplore.ieee.org Open Access | IEEE Access Open Access | IEEE Access Open Access | ISTI Repository Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | IEEE Access Open Access


2020 Journal article Open Access OPEN

Thermal vulnerability detection in integrated electronic and photonic circuits using infrared thermography
Hussain B., Jalil B., Pascali M. A., Imran M., Serafino G., Moroni D., Ghelfi P.
Failure prediction of any electrical/optical component is crucial for estimating its operating life. Using high temperature operating life (HTOL) tests, it is possible to model the failure mechanisms for integrated circuits. Conventional HTOL standards are not suitable for operating life prediction of photonic components owing to their functional dependence on the thermo-optic effect. This work presents an infrared (IR)-assisted thermal vulnerability detection technique suitable for photonic as well as electronic components. By accurately mapping the thermal profile of an integrated circuit under a stress condition, it is possible to precisely locate the heat center for predicting the long-term operational failures within the device under test. For the first time, the reliability testing is extended to a fully functional microwave photonic system using conventional IR thermography. By applying image fusion using affine transformation on multimodal acquisition, it was demonstrated that by comparing the IR profile and GDSII layout, it is possible to accurately locate the heat centers along with spatial information on the type of component. Multiple IR profiles of optical as well as electrical components/circuits were acquired and mapped onto the layout files. In order to ascertain the degree of effectiveness of the proposed technique, IR profiles of complementary metal-oxide semiconductor RF and digital circuits were also analyzed. The presented technique offers a reliable automated identification of heat spots within a circuit/system.Source: Applied optics (2004, Online) 59 (2020): E97–E106. doi:10.1364/AO.389960
DOI: 10.1364/ao.389960

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2020 Report Open Access OPEN

Final Report on IAPR TC16
Moroni D., Pascali M. A., Paulus D., Yashina V., Gurevich I.
The report accounts for the activities of TC16 on "Algebraic and Discrete Mathematical Techniques in Pattern Recognition and Image Analysis" of the International Association for Pattern Recognition during the term 2019-2020.Source: ISTI Annual reports, 2020

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2019 Journal article Open Access OPEN

Visible and infrared imaging based inspection of power installation
Jalil B., Pascali M. A., Leone G. R., Martinelli M., Moroni D., Salvetti O., Berton A.
The inspection of power lines is the crucial task for the safe operation of power transmission: its components require regular checking to detect damages and faults that are caused by corrosion or any other environmental agents and mechanical stress. During recent years, the use of Unmanned Autonomous Vehicle (UAV) for environmental and industrial monitoring is constantly growing and the demand for fast and robust algorithms for the analysis of the data acquired by drones during the inspections has increased. In this work, we use UAV to acquire power transmission lines data and apply image processing to highlight expected faults. Our method is based on a fusion algorithm for the infrared and visible power lines images, which is invariant to large scale changes and illumination changes in the real operating environment. Hence, different algorithms from image processing are applied to visible and infrared thermal data, to track the power lines and to detect faults and anomalies. The method significantly identifies edges and hot spots from the set of frames with good accuracy. At the final stage we identify hot spots using thermal images. The paper concludes with the description of the current work, which has been carried out in a research project, namely SCIADRO.Source: Pattern recognition and image analysis 29 (2019): 35–41. doi:10.1134/S1054661819010140
DOI: 10.1134/s1054661819010140

See at: ISTI Repository Open Access | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | CNR ExploRA Restricted


2019 Conference article Open Access OPEN

Architectural Heritage: 3D Documentation and Structural Monitoring Using UAV
Germanese D, Pascali M. A., Berton A., Leone G. R., Moroni D., Jalil B., Tampucci M., Benassi A.
Architectural heritage preservation and dissemination is a very important topic in Cultural Heritage. Since ancient structures may present areas which are dangerous or difficult to access, Unmanned Aerial Vehicles may be a smart solution for the safe and fast data acquisition. In this paper, we propose a method for the long term monitoring of cracking patterns, based on image processing and marker-based technique. Also the paper includes the description of a pipeline for the reconstruction of interactive 3D scene of the historic structure to disseminate the acquired data, to provide the general public with info regarding the structural health of the structure, and possibly to support the drone pilot during the survey. The Introduction provides a state of the art about the crack monitoring from visible images; it follows a description of the proposed method, and the results of the experimentation carried out in a real case study (the Ancient Fortress in Livorno, Italy). A specific section is devoted to the description of the front-end of augmented reality designed for heritage dissemination and to support the drone usage. Details about the future works conclude the paper.Source: Visual Pattern Extraction and Recognition for Cultural Heritage Understanding (VIPERC 2019), pp. 1–12, Pisa, January 30, 2019

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2019 Journal article Open Access OPEN

Fault detection in power equipment via an unmanned aerial system using multi modal data
Jalil B., Leone G. R., Martinelli M., Moroni M., Pascali M. A., Berton A.
The power transmission lines are the link between the power plants and the points of consumption, through substations. Most importantly, the assessment of damaged aerial power lines and rusted conductors is of extreme importance for public safety; hence, power line and associated components must be periodically inspected to ensure a continuous supply and to identify any fault and defect. To achieve these objectives, recently Unmanned Aerial Vehicles (UAVs) have been widely used: in fact, they provide a safe way to bring sensors close to the power transmission lines and their associated components without halting the equipment during the inspection, and reducing operational cost and risk. In this work, the drone, equipped with multi-modal sensors, captures images in the visible and infrared domain and transmits them to the ground station. We used state-of-the-art computer vision methods to highlight expected faults (i.e. hot spots) or damaged components of the electrical infrastructure (i.e. damaged insulators). Infrared imaging, which is invariant to large scale and illumination changes in the real operating environment, supported the identification of faults in power transmission lines; while a neural network is adapted and trained to detect and classify insulators from an optical video stream. We demonstrate our approach on the data captured by a drone in Parma, Italy.Source: Sensors (Basel) 19 (2019). doi:10.3390/s19133014
DOI: 10.3390/s19133014

See at: Sensors Open Access | Sensors Open Access | Europe PubMed Central Open Access | Sensors Open Access | Sensors Open Access | ISTI Repository Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Sensors Open Access | Sensors Open Access | Sensors Open Access | Sensors Open Access | ZENODO Open Access | Hyper Article en Ligne Restricted | Hyper Article en Ligne Restricted | Hyper Article en Ligne Restricted


2019 Conference article Open Access OPEN

A preliminary study for a marker-based crack monitoring in ancient structures
Germanese D., Pascali M. A., Berton A., Leone G. R., Jalil B., Moroni D., Salvetti O., Tampucci M.
Historical buildings are undeniably valuable documents of the history of the world. Their preservation has attracted considerable attention among modern societies, being a major issues both from economical and cultural point of view. This paper describes how image processing and marker-based application may support the long-term monitoring of crack patterns in the context of cultural heritage preservation, with a special focus on ancient structures. In detail, this work includes a state of the art about the most used techniques in structural monitoring, a description of the proposed methodology and the experimentation details. A discussion about the results and future works concludes the paper.Source: 2nd International Conference on Applications of Intelligent Systems, Las Palmas de Gran Canaria, Spain, 07-09 January 2019
DOI: 10.1145/3309772.3309795

See at: dl.acm.org Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | dl.acm.org Restricted


2019 Journal article Open Access OPEN

A preliminary study on non contact thermal monitoring of microwave photonic systems
Jalil B., Hussain B., Pascali M. A., Serafino G., Moroni D., Ghelfi P.
Microwave photonic systems are more susceptible to thermal fluctuations due to thermo-optic effect. In order to stabilize the performance of photonic components, thermal monitoring is achieved by using thermistors placed at any arbitrary location along the component. This work presents non contact thermography of a fully functional microwave photonic system. The temperature profile of printed circuit board (PCB) and photonic integrated circuit (PIC) is obtained using Fluke FLIR (A65) camera. We performed Otsu's thresholding to segment heat centers located across PCB as well as PIC. The infrared and visible cameras used in this work have different field of view, therefore, after applying morphological methods, we performed image registration to synchronize both visible and thermal images. We demonstrate this method on the circuit board with active electrical/photonic elements and were able to observe thermal profile of these components.Source: Proceedings (MDPI) 27 (2019). doi:10.3390/proceedings2019027019
DOI: 10.3390/proceedings2019027019

See at: Proceedings Open Access | Archivio della ricerca della Scuola Superiore Sant'Anna Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Proceedings Open Access | Proceedings Open Access


2019 Conference article Open Access OPEN

La radiomica come elemento fondante della medicina di precisione in ambito oncologico
Colantonio S., Carlini E., Caudai C., Germanese D., Manghi P., Pascali M. A., Barucci A., Farnesi D., Zoppetti N., Colcelli V., Pini R., Carpi R., Esposito M., Neri E., Romei C., Occhipinti M.
Questo documento introduce e inquadra le attività che un gruppo interdisciplinare di ricercatori e clinici sta portando avanti grazie a tecniche di analisi di immagini, machine learning e intelligenza artificiale, a supporto della medicina di precisione in ambito oncologico. Partendo dalla comprensione del fenomeno fisico e dalla caratterizzazione dei processi biologici che sottendono alla formazione delle immagini biomedicali, attraverso tecniche di analisi radiomica dei dati radiologici e di mining di dati complessi, terogenei e multisorgente, le soluzioni studiate mirano a supportare i clinici nel continuum dei processi diagnostici, prognostici e terapeutici in ambito oncologico.Source: Ital-IA: primo Convegno Nazionale CINI sull'Intelligenza Artificiale, Roma, Italy, 18-19 marzo 2019

See at: ISTI Repository Open Access | CNR ExploRA Open Access | www.ital-ia.it Open Access


2019 Conference article Restricted

Radiomics to predict prostate cancer aggressiveness: a preliminary study
Germanese D., Mercatelli L., Colantonio S., Miele V., Pascali M. A., Caudai C., Zoppetti N., Carpi R., Barucci A., Bertelli E., Agostini S.
Radiomics is encouraging a paradigm shift in oncological diagnostics towards the symbiosis of radiology and Artificial Intelligence (AI) techniques. The aim is to exploit very accurate, robust image processing algorithms and provide quantitative information about the phenotypic differences of cancer traits. By exploring the association between this quantitative information and patients' prognosis, AI algorithms are boosting the power of radiomics in the perspective of precision oncology. However, the choice of the most suitable AI method can determine the success of a radiomic application. The current state-of-the art methods in radiomics aim at extracting statistical features from biomedical images and, then, process them with Machine Learning (ML) techniques. Many works have been reported in the literature presenting various combinations of radiomic features and ML methods. In this preliminary study, we aim to analyse the performance of a radiomic approach to predict prostate cancer (PCa) aggressiveness from multiarametric Magnetic Resonance Imaging (mp-MRI). Clinical mp-MRI data were collected from patients with histology-confirmed PCa and labelled by a team of expert radiologists. Such data were used to extract and select two sets of radiomic features; hence, the classification performances of five classifiers were assessed. This analysis is meant as a preliminary step towards the overall goal of investigating the potential of radiomic-based analyses.Source: BIBE 2019: 19th annual IEEE International Conference on Bioinformatics and Bioengineering, pp. 972–976, Athens, Greece, 28-30 October 2019
DOI: 10.1109/bibe.2019.00181

See at: academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted | xplorestaging.ieee.org Restricted


2019 Conference article Open Access OPEN

Metodologie di visione artificiale per la documentazione e il monitoraggio strutturale di costruzioni antiche mediante droni
Leone G. R., Germanese D., Moroni D., Pascali M. A., Tampucci M., Berton A.
La manutenzione e la salvaguardia del complesso patrimonio architettonico italiano rappresentano un'importante sfida che deve essere quotidianamente affrontata dalle soprintendenze e dalla amministrazioni locali e regionali. In quest'ambito, lo sviluppo delle tecnologie ICT può contribuire ad una gestione più efficiente e accurata del costruito storico. In questo intervento, si presenta un sistema di visione artificiale basato sull'utilizzo di droni che permette di monitorare lo stato di conservazione di edifici e strutture nel tempo, andando a quantificare l'entità di lesioni e ammaloramenti. Un frontend di realtà virtuale, ottenuto mediante tecniche fotogrammetriche, permette inoltre di visualizzare i dati trasmessi dal drone contestualmente ai dati raccolti da una rete di sensori wireless per il monitoraggio in situ delle strutture. Il sistema è stato testato in tre diversi casi di studio in Toscana.Source: Ital-IA 2019, primo Convegno Nazionale CINI sull'Intelligenza Artificiale, WORKSHOP AI for CULTURAL HERITAGE, Roma, 18-19 Marzo 2019

See at: ISTI Repository Open Access | CNR ExploRA Open Access | www.ital-ia.it Open Access


2019 Conference article Open Access OPEN

May radiomic data predict prostate cancer aggressiveness?
Germanese D., Colantonio S., Caudai C., Pascali M. A., Barucci A., Zoppetti N., Agostini S., Bertelli E., Mercatelli L., Miele V., Carpi R.
Radiomics can quantify tumor phenotypic characteristics non-invasively by defining a signature correlated with biological information. Thanks to algorithms derived from computer vision to extract features from images, and machine learning methods to mine data, Radiomics is the perfect case study of application of Artificial Intelligence in the context of precision medicine. In this study we investigated the association between radiomic features extracted from multi-parametric magnetic resonance imaging (mp-MRI)of prostate cancer (PCa) and the tumor histologic subtypes (using Gleason Score) using machine learning algorithms, in order to identify which of the mp-MRI derived radiomic features can distinguish high and low risk PCa.Source: CAIP 2019 - International Conference on Computer Analysis of Images and Patterns, pp. 65–75, Salerno, Italy, 6 September, 2019
DOI: 10.1007/978-3-030-29930-9_7

See at: ISTI Repository Open Access | academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted


2018 Conference article Open Access OPEN

UAVs and UAV swarms for civilian applications: communications and image processing in the SCIADRO project
Bacco M., Chessa S., Di Benedetto M., Fabbri D., Girolami M., Gotta A., Moroni D., Pascali M. A., Pellegrini V.
The use of Unmanned Aerial Vehicles (UAVs), or drones, is increasingly common in both research and industrial fields. Nowadays, the use of single UAVs is quite established and several products are already available to consumers, while UAV swarms are still subject of research and development. This position paper describes the objectives of a research project, namely SCIADRO2, which deals with innovative applications and network architectures based on the use of UAVs and UAV swarms in several civilian fields.Source: WiSATS 2017 - International Conference on Wireless and Satellite Systems, pp. 115–124, Oxford, UK, 14-15 September 2017
DOI: 10.1007/978-3-319-76571-6_12

See at: ISTI Repository Open Access | academic.microsoft.com Restricted | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted | rd.springer.com Restricted


2018 Journal article Open Access OPEN

Computational topology to monitor human occupancy
Barsocchi P., Cassará P., Giorgi D., Moroni D., Pascali M. A.
The recent advances in sensing technologies, embedded systems, and wireless communication technologies, make it possible to develop smart systems to monitor human activities continuously. The occupancy of specific areas or rooms in a smart building is an important piece of information, to infer the behavior of people, or to trigger an advanced surveillancemodule. We propose a method based on computational topology to infer the occupancy of a room monitored for a week by a system of low-cost sensors.Source: Proceedings (MDPI) 2 (2018). doi:10.3390/proceedings2020099
DOI: 10.3390/proceedings2020099
DOI: 10.5281/zenodo.1159170
DOI: 10.5281/zenodo.1159169

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2018 Conference article Open Access OPEN

To identify hot spots in power lines using infrared and visible sensors
Jalil B., Pascali M. A., Leone G. R, Martinelli M., Moroni D., Salvetti O.
The detection of power transmission lines is highly important for threat avoidance, especially when aerial vehicle fly at low altitude. At the same time, the demand for fast and robust algorithms for the analysis of data acquired by drones during inspections has also increased. In this paper, different methods to obtain these objectives are presented, which include three parts: sensor fusion, power line extraction and fault detection. At first, fusion algorithm for visible and infrared power line images is presented. Manual control points describe as feature points from both images were selected and then, applied geometric transformation model to register visible and infrared thermal images. For the extraction of power lines, we applied Canny edge detection to identify significant transition followed by Hough transform to highlight power lines. The method significantly identify edges from the set of frames with good accuracy. After the detection of lines, we applied histogram based thresholding to identify hot spots in power lines. The paper concludes with the description of the current work, which has been carried out in a research project, namely SCIADRO.Source: MISSI 2018 - International Conference on Multimedia and Network Information System, pp. 313–321, Wroclaw, Poland, 11-14 September 2018
DOI: 10.1007/978-3-319-98678-4_32

See at: ISTI Repository Open Access | ISTI Repository Open Access | academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | doi.org Restricted | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted | rd.springer.com Restricted


2018 Conference article Open Access OPEN

Multimodal image analysis for power line inspection
Jalil B., Leone G. R., Martinelli M., Moroni D., Pascali M. A., Salvetti O.
he use of Unmanned Aerial Vehicles (UAVs) for environmental and industrial monitoring is constantly growing. At the same time, the demand for fast and robust algorithms for the analysis of the data acquired by drones during the inspections has increased. In this paper we provide a concise survey about a peculiar case study: the monitoring of the high-voltage power grid which includes: (i) the detection of the power lines and of the electric towers along with their components more subject to wear and tear; (ii) the diagnosis of maintenance status. In this work different algorithms from image processing are applied to visible and infrared thermal data, to track the power lines and to detect faults and anomalies. We applied Canny edge detection to identify significant transition followed by Hough transform to highlight power lines. The method significantly identify edges from the set of frames with good accuracy. The paper concludes with the description of the current work, which has been carried out in a research project, namely SCIADRO.Source: ICPRAI 2018 - International Conference on Pattern Recognition and Artificial Intelligence, pp. 592–596, Montreal, Canada, 14-17 May 2018

See at: ISTI Repository Open Access | CNR ExploRA | users.encs.concordia.ca


2018 Conference article Open Access OPEN

Towards structural monitoring and 3D documentation of architectural heritage using UAV
Germanese D., Leone G. R., Moroni D., Pascali M. A., Tampucci M.
This paper describes how UAVs may support the architectural heritage preservation and dissemination. In detail, this work deals with the long-term monitoring of the crack pattern of historic structures, and with the reconstruction of interactive 3D scene in order to provide both the scholar and the general public with a simple and engaging tool to analyze or visit the historic structure.Source: MISSI 2018 - International Conference on Multimedia & Network Information Systems, pp. 332–342, Wrocraw, Poland, 12-14 September 2018
DOI: 10.1007/978-3-319-98678-4_34

See at: ISTI Repository Open Access | academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | doi.org Restricted | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted