Pubblicazioni di Mario Molinara

Machine Learning for Non-Intrusive Profiling of IoT Devices in Noisy Environments

Shervin Shirmohammadi, University of Ottawa, Canada Marco Carratù, University of Salerno, Italy Ruqiang Yan, Xi’an Jiaotong University, China, Rega V., Tari L., Capriglione D., Molinara M., Pace C. D., Marignetti F., Pace C.D.

Lightweight Machine Learning Pipeline for WGM Micro-Laser Sensing: A Feasibility Study on IFN-γ Detection

IEEE, Miele A., Milano F., Molinara M., Ferrigno L., Ferretti S., Ghofraniha N.

Machine-Learning-Based Color Sensing Using Wearable SENSIPATCH Spectrometer Module: An Experimental Study

SENSORS, Mustafa H., Fina F., Molinara M., Ferrigno L., Ria A., Bruschi P., Contardi S., Leccese F., Mustafa H. T., Mustafa H.T.

State-of-Health Estimation for Lithium-Ion Batteries Using Lightweight Features from the Constant Current Charging Phase

Pietrocola G., Porpora F., Molinara M., Gerevini L., Vitelli M., Marrocco C., Bria A.

Poseidon: A ViT-based Architecture for Multi-Frame Pose Estimation with Adaptive Frame Weighting and Multi-Scale Feature Fusion

Pace, C. D., De Nunzio, A. M., De Stefano, C., Fontanella, F., Molinara, M., Pace, C.D., De Nunzio, A.M.

A Deep Learning System for Water Pollutant Detection Based on the SENSIPLUS Microsensor

Mustafa H., Molinara M., Ferrigno L., Vitelli M.

Evaluation of Deep Learning Models for State of Charge Estimation for Lithium Batteries Using Image-Encoded Electrochemical Impedance Spectroscopy Data

Mustafa, H., Vitelli, M., Milano, F., Molinara, M., Ferrigno, L.

Side-Channel Measurements and Machine Learning for Classifying Application-Level Scenarios in IoT Contexts

IEEE, Rega, Vincenzo, Tari, Luca, Capriglione, Domenico, Molinara, Mario, Marignetti, Fabrizio

Machine Learning and Genetic Programming-based behavioral modeling approaches of Li-ion Batteries

IEEE, Di Capua, Giulia, Molinara, Mario, Maffucci, Antonio, Porpora, Francesco, Femia, Nicola, Oliva, Nunzio

Markerless Gait Analysis for Parkinson’s disease diagnosis: A study on machine learning integration and features explainability

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, Pace, Cesare Davide, De Nunzio, Alessandro Marco, De Stefano, Claudio, Fontanella, Francesco, Molinara, Mario

Markerless Machine Learning Approach for Gait Classification in Knee Osteoarthritis

Palaiahnakote, Schuckers, Ogier, JM., Bhattacharya, Pal, Pace, Cesare Davide, De Nunzio, Alessandro Marco, De Stefrano, Claudio, Fontanella, Francesco, Molinara, Mario

A Deep Transfer Learning Approach for Writer Identification in Greek Papyri

D'Alessandro, T., Cilia, N. D., De Stefano, C., Fontanella, F., Molinara, M., Scotto di Freca, A., Marthot-Santaniello, I.

Artificial intelligence-assisted electrochemical sensors for qualitative and semi-quantitative multiplexed analyses

DIGITAL DISCOVERY, Cancelliere R., Molinara M., Licheri A., Maffucci A., Micheli L., CUP H53D23000520006

Preliminary Evaluation of Machine Learning Approaches for PANTONE Color Classification with the SENSIPATCH wearable system

IEEE, Mustafa, Hamza, Vitelli, Michele, Milano, Filippo, Molinara, Mario, Ferrigno, Luigi, Ria, Andrea, Fina, Federico, Leccese, Fabio

Numerical modeling for lithium iron phosphate batteries

IEEE, Palmieri, B., Martone, A., Miele, A., Milano, F., Molinara, M., Ferrigno, L., Cerro, G., Laracca, M.

Profiling Running Applications in Connected Devices Through Side-Channel and Machine Learning Techniques

IEEE ACCESS, Rega V., Capriglione D., Marignetti F., Molinara M., Amodei A.

UniCas for Industry

CEUR-WS, Alessio Miele, Hamza Mustafa, Michele Vitelli, Alessandro Bria, Claudio De Stefano, Francesco Fontanella, Claudio Marrocco, Mario Molinara, Alessandra Scotto di Freca, Miele A., Mustafa H., Vitelli M., Bria A., De Stefano C., Fontanella F., Marrocco C., Molinaria M., di Freca A.S., corda_____he::de1cc9242568d954beba138f12d7aec1

SENSIBUS: A Novel One Wire Protocol for Smart Sensors

IEEE, Balocchi L., Vitelli M., Molinara M., Bonafoni S., Roselli L., Contardi S., Nannipieri I.

UniCas for Medicine and Healthcare

Carlo Sansone, Cantone M., Galasso S., Lozupone G., Nardone E., Pace C. D., Russo C., Bria A., D'Alessandro T., De Stefano C., Fontanella F., Marrocco C., Molinara M., di Freca A. S., Pace C.D., di Freca A.S.

Comparative Analysis of SoC Estimation in Batteries using SFRA and EIS

Paolo Attilio Pegoraro, Miele A., Vitelli M., Sardellitti A., Milano F., Molinara M., Ferrigno L., Ciancetta F., Mari S.

A novel measurement procedure for error correction in single camera gait analysis

Svonko Galasso, SVONKO GALASSO, CHIARA CARISSIMO, GIANNI CERRO, MARIO MOLINARA, LUIGI FERRIGNO, ROCCO SALVATORE CALABRÒ, ALESSANDRO MARCO DE NUNZIO, IEEE ACCESS, Galasso S., Carissimo C., Cerro G., Molinara M., Ferrigno L., Calabro R. S., De Nunzio A. M., Calabro R.S., De Nunzio A.M.

Transfer learning in breast mass detection and classification

Ryspayeva, Marya, Bria, Alessandro, Marrocco, Claudio, Tortorella, Francesco, Molinara, Mario, Ryspayeva M., Bria A., Marrocco C., Tortorella F., Molinara M.

SoC estimation on Li-ion batteries: A new EIS-based dataset for data-driven applications

Hamza Mustafa, DATA IN BRIEF, Mustafa H., Bourelly C., Vitelli M., Milano F., Molinara M., Ferrigno L.

Breast Mass Detection and Classification Using Transfer Learning on OPTIMAM Dataset Through RadImageNet Weights

Kassahun R. K., Molinara M., Bria A., Marrocco C., Tortorella F., Kassahun R.K.

A Novel Writer Identification Approach for Greek Papyri Images

Cilia N. D., D'Alessandro T., De Stefano C., Fontanella F., Marthot-Santaniello I., Molinara M., Scotto Di Freca A., Cilia N.D.

Illegal Microdumps Detection in Multi-Mission Satellite Images With Deep Neural Network and Transfer Learning Approach

IEEE ACCESS, Marrocco C., Bria A., Tortorella F., Parrilli S., Cicala L., Focareta M., Meoli G., Molinara M.

End-to-End Asbestos Roof Detection on Orthophotos Using Transformer-Based YOLO Deep Neural Network

Foresti, G.L., Fusiello, Hancock, Pace, Cesare Davide, Bria, Alessandro, Focareta, Mariano, Lozupone, Gabriele, Marrocco, Claudio, Meoli, Giuseppe, Molinara, Mario

Transfer Learning in Breast Mass Detection on the OMI-DB Dataset: A Preliminary Study

Jean-Jacques Rousseau, Bill Kapralos, Ryspayeva, Marya, Molinara, Mario, Bria, Alessandro, Marrocco, Claudio, Tortorella, Francesco

Load Profile Analysis in Electrical Systems: The Impact of Electrical Signature and Monitoring Quality in the Energy Digitalization Process

Tari L., Molinara M., Ferrigno L.

EIS-Based SoC Estimation: A Novel Measurement Method for Optimizing Accuracy and Measurement Time

Filippo Milano, IEEE ACCESS, Bourelly, Carmine, Vitelli, Michele, Milano, Filippo, Molinara, Mario, Fontanella, Francesco, Ferrigno, Luigi

A Statistical Approach for Electrochemical Impedance Spectroscopy Analysis on LFP Batteries’ State of Charge

IEEE, Tari, L., Bourelly, C., Vitelli, M., Milano, F., Molinara, M., Ferrigno, L.

Predicting physical activity levels from kinematic gait data using machine learning techniques

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, Galasso S., Baptista R., Molinara M., Pizzocaro S., Calabro R. S., De Nunzio A. M., Calabro R.S., De Nunzio A.M.

GA-Based Features Selection for Electro-chemical Impedance Spectroscopy on Lithium Iron Phosphate Batteries

IEEE, Bourelly C., Vitelli M., Milano F., Molinara M., Fontanella F., Ferrigno L.

Detection of Wastewater Pollution through Natural Language Generation with a Low-Cost Sensing Platform

IEEE ACCESS, Roitero K., Portelli B., Serra G., Mea V. D., Mizzaro S., Cerro G., Vitelli M., Molinara M., Mea V.D.

Modeling of Ferrite Inductors Power Loss Based on Genetic Programming and Neural Networks

COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE, C. De Stefano, F. Fontanella, L. Vanneschi, Giulia Di Capua, Mario Molinara, Francesco Fontanella, Claudio De Stefano, Nunzio Oliva, Nicola Femia

SENSIPLUS-LM: A Low-Cost EIS-Enabled Microchip Enhanced with an Open-Source Tiny Machine Learning Toolchain

COMPUTERS, Vitelli M., Cerro G., Gerevini L., Miele G., Ria A., Molinara M.

Transformer-based mass detection in digital mammograms

Betancourt Tarifa A. S., Marrocco C., Molinara M., Tortorella F., Bria A., Betancourt Tarifa A.S.

An end-to-end real-time pollutants spilling recognition in wastewater based on the IoT-ready SENSIPLUS platform

Mario Molinara, Luca Gerevini, Gianni Cerro, Alessandro Bria, Claudio Marrocco, Luigi Ferrigno, Michele Vitelli, Andrea Ria, MAGALAT GAMʼAT AL-MALIK SAUD: ULM AL-HASIB WA AL-MAʼLUMAT, Gerevini L., Cerro G., Bria A., Marrocco C., Ferrigno L., Vitelli M., Ria A., Molinara M.

Using Genetic Programming to Learn Behavioral Models of Lithium Batteries

J. Correia, S. Smith, R. Qaddoura, Giulia Di Capua, Carmine Bourelly, Claudio De Stefano, Francesco Fontanella, Filippo Milano, Mario Molinara, Nunzio Oliva, Francesco Porpora

A new Dataset for Detection of Illegal or Suspicious Spilling in Wastewater through Low-cost Real-time Sensors

IEEE, Mario Molinara, Carmine Bourelly, Luigi Ferrigno, Luca Gerevini, M. Vitelli, A. Ria, F. Magliocca, L. Ruscitti, R. Simmarano, A. Trynda, P. Olejnik, Molinara M., Bourelly C., Ferrigno L., Gerevini L., Vitelli M., Ria A., Magliocca F., Ruscitti L., Simmarano R., Trynda A., Olejnik P.

An Open Source C Code Generator and a Tiny Machine Learning Toolchain for the SENSIPLUS Platform

Valérie Issarny, Stephan Sigg, Chiara Boldrini, Simone Silvestri, Bria A., Ferrigno L., Marrocco C., Molinara M., Vitelli M., Ria A., Cicalini M., Manfredini G., Bruschi P.

A Deep Transfer Learning Approach to an Effective Classification of Water Pollutants From Voltammetric Characterizations

Guido Ala, Sergio Rapuano, Tiziana Tambosso, Molinara M., Ferrigno L., Maffucci A., Kuzhir P., Cancelliere R., Tinno A. D., Micheli L., Shuba M., Tinno A.D.

A Deep Learning Approach to Organic Pollutants Classification Using Voltammetry

Mario Molinara, SENSORS, Molinara, Mario, Cancelliere, Rocco, Di Tinno, Alessio, Ferrigno, Luigi, Shuba, Mikhail, Kuzhir, Polina, Maffucci, Antonio, Micheli, Laura

Management and Sustainable Exploitation of Marine Environments through Smart Monitoring and Automation

Glaviano F., Esposito R., Di Cosmo A., Esposito F., Gerevini L., Ria A., Molinara M., Bruschi P., Costantini M., Zupo V.

Evolutionary Computation to Implement an IoT-Based System for Water Pollution Detection

SN COMPUTER SCIENCE, De Stefano, Claudio, Ferrigno, Luigi, Fontanella, Francesco, Gerevini, Luca, Molinara, Mario

A Novel Evolutionary Approach for IoT-Based Water Contaminant Detection

De Stefano C., Ferrigno L., Fontanella F., Gerevini L., Molinara M.

An ASIC-based miniaturized system for online multi-measurand monitoring of lithium-ion batteries

Manfredini G., Ria A., Bruschi P., Gerevini L., Vitelli M., Molinara M., Piotto M., BATTERIES

Artificial intelligence for distributed smart systems

Molinara M.,, Bria A., De Vito S., Marrocco C., PATTERN RECOGNITION LETTERS, Molinara M.

A False Positive Reduction System for Continuous Water Quality Monitoring

Bria A., Ferrigno L., Gerevini L., Marrocco C., Molinara M., Bruschi P., Cicalini M., Manfredini G., Ria A., Cerro G., Simmarano R., Teolis G., Vitelli M.

From Online Handwriting to Synthetic Images for Alzheimer's Disease Detection Using a Deep Transfer Learning Approach

Cilia N. D., D'Alessandro T., De Stefano C., Fontanella F., Molinara M.

HeGo, a social game as a tool for cultural heritage valorization: the case study of the Atina historical center

F. FONTANELLA, M. MOLINARA, A. GALLOZZI, M. CIGOLA, L. J. SENATORE, R. FLORIO, P. CLINI, F. CELIS D’AMICO

Chemicals Detection in Water by SENSIPLUS Platform: Current State and Ongoing Progress

Bourelly C., Ferdinandi M., Molinara M., Ferrigno L., Simmarano R.

A Fast Gas Sensing Layer Working at Room Temperature for IOT in Air Quality Scenario

Massera E., Alfano B., Miglietta M. L., Polichetti T., De Vito S., Formisano F., Di Francia G., Delli Veneri P., Ferdinandi M., Molinara M., Miglietta M.L.

A Preliminary Solution for Anomaly Detection in Water Quality Monitoring

Paolo Bellavista, Qi Han, Bourelly C., Bria A., Ferrigno L., Gerevini L., Marrocco C., Molinara M., Cerro G., Cicalini M., Ria A.

Deep Transfer Learning for Alzheimer's disease detection

A. Del Bimbo et. al., Cilia N. D., de Stefano C., Marrocco C., Fontanella F., Molinara M., Scotto di Freca A.

An Experimental Comparison between Deep Learning and Classical Machine Learning Approaches for Writer Identification in Medieval Documents

Francesco Fontanella, Nicole Dalia Cilia, Claudio De Stefano, Claudio Marrocco, Mario Molinara, Alessandra Scotto di Freca, Cilia, Nicole Dalia, De Stefano, Claudio, Fontanella, Francesco, Marrocco, Claudio, Molinara, Mario, Scotto di Freca, Alessandra

Pattern recognition and artificial intelligence techniques for cultural heritage

F. Fontanella, F. Colace, A. Scotto Di Freca, F. Stanco, PATTERN RECOGNITION LETTERS, Fontanella F., Colace F., Molinara M., Scotto Di Freca A., Stanco F.

An IoT-ready solution for automated recognition of water contaminants

Mario Molinara, Alessandro Bria, Gianni Cerro, Claudio Marrocco, Marco Ferdinandi, PATTERN RECOGNITION LETTERS, Bria A., Cerro G., Ferdinandi M., Marrocco C., Molinara M.

An End to End Indoor Air Monitoring System Based on Machine Learning and SENSIPLUS Platform

IEEE ACCESS, Molinara M., Ferdinandi M., Cerro G., Ferrigno L., Massera E., The work was supported in part by the European Union’s Horizon 2020 Research and Innovation Programme under Agreement 787128, and in part by the Minister for Education, University and Research (MIUR) Law, Department of Excellence under Grant 232/216

A multi-context CNN ensemble for small lesion detection

Savelli B., Bria A., Marrocco C., Tortorella F, Molinara M., ARTIFICIAL INTELLIGENCE IN MEDICINE

What is the minimum training data size to reliably identify writers in medieval manuscripts?

Nicole Dalia Cilia, Claudio De Stefano, Francesco Fontanella, Mario Molinara, Alessandra Scotto di Freca, PATTERN RECOGNITION LETTERS, Cilia N. D., De Stefano C., Fontanella F., Molinara M., Scotto di Freca A.

An end-to-end deep learning system for medieval writer identification

Cilia Nicole Dalia, De Stefano Claudio, Fontanella Francesco, Claudio Marrocco, Alessandra Scotto Di Freca, PATTERN RECOGNITION LETTERS, Cilia N. D., De Stefano C., Fontanella F., Marrocco C., Molinara M., Scotto Di Freca A.

SENSIPLUS: An Innovative Solution for Health and Safety Applications

Vari, G. Betta, G. Cerro, M. Ferdinandi, L. Ferrigno, M. Laracca, M. Molinara

Handwriting Analysis to Support Alzheimer’s Disease Diagnosis: A Preliminary Study

Cilia N. D., De Stefano C., Fontanella F., Molinara M., Scotto Di Freca A.

Minimizing Training Data for Reliable Writer Identification in Medieval Manuscripts

Cilia N. D., De Stefano C., Fontanella F., Molinara M., Scotto di Freca A.

Rilievo e valorizzazione dei centri storici minori gamification e structure from motion

P.Fiore, E. D’Andria (Eds.), M. Cigola, T. Della Corte, F. Fontanella, A. Gallozzi, S. Gargaro, M. Molinara, R. Quattrini, L. J. Senatore, R. M. Strollo

A Page-Based Reject Option for Writer Identification in Medieval Books

Elisa Ricci, Samuel Rota Bulò, Cees Snoek, Oswald Lanz, Stefano Messelodi, Nicu Sebe, Cilia N. D., De Stefano C., Fontanella F., Marrocco C., Molinara M., Scotto di Freca A.

Minimizing Training Data for Reliable Writer Identification in Medieval Manuscripts

Elisa Ricci, Samuel Rota Bulò, Cees Snoek, Oswald Lanz, Stefano Messelodi, Nicu Sebe, Cilia N. D., De Stefano C., Fontanella F., Molinara M., Scotto di Freca A.

Combining convolutional neural networks for multi-context microcalcification detection in mammograms

COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE, Mario Vento, Gennaro Percannella, Savelli B., Marrocco C., Bria A., Molinara M., Tortorella F.

Using handwriting features to characterize cognitive impairment

Cilia N. D., De Stefano C., Fontanella F., Molinara M., Scotto Di Freca A.

Contaminants detection and classification through a customized IoT-based platform: A case study

Gianni Cerro, Giovanni Betta, Marco Ferdinandi, Luigi Ferrigno, Mario Molinara, IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE, Betta, Giovanni, Cerro, Gianni, Ferdinandi, Marco, Ferrigno, Luigi, Molinara, Mario, Horizon 2020 research and innovation programme under grant agreement SYSTEM No. 787128

A novel smart system for contaminants detection and recognition in water

Smartcomp 2019, Ferdinandi M., Molinara M., Cerro G., Ferrigno L., Claudio Marrocco, Bria A., Di Meo P., Bourelly C., Simmarano R.

Survey and Valorisation of The Historical Centres Gamification And Structure From Motion.

P.Fiore, E. D’Andria (Eds.), M. Cigola, T. Della Corte, F. Fontanella, A. Gallozzi, S. Gargaro, M. Molinara, R. Quattrini, L. J. Senatore, R. M. Strollo

A Two-Step System Based on Deep Transfer Learning for Writer Identification in Medieval Books

Cilia, Nicole Dalia, De Stefano, Claudio, Fontanella, Francesco, Marrocco, Claudio, Molinara, Mario, Scotto Di Freca, Alessandra

HeritageGO (HeGO): A Social Media Based Project for Cultural Heritage Valorization

ACM SIGCHI & ACM SIGWEB, Fontanella Francesco, Molinara Mario, Gallozzi Arturo, Cigola Michela, Senatore LucaJ., Florio Riccardo, Clini Paolo, Celis D'Amico Flavio

Automatic Writer Identification in Medieval Books

P. Daponte and M. Maniaci, De Stefano, Claudio, Fontanella, Francesco, Maniaci, Marilena, Marrocco, Claudio, Molinara, Mario, Scotto di Freca, Alessandra

Deep Transfer Learning for writer identification in medieval books

P. Daponte and M. Maniaci, Bria, Alessandro, Cilia, Nicole Dalia, De Stefano, Claudio, Fontanella, Francesco, Marrocco, Claudio, Molinara, Mario, Scotto di Freca, Alessandra, Tortorella, Francesco

SENSIPLUS: AN INNOVATIVE PLATFORM FOR HEALTH AND SAFETY APPLICATIONS IN SMART CITIES

Vari, G. Cerro, M. Ferdinandi, L. Ferrigno, M. Laracca, M. Molinara

A deep learning framework for micro-calcification detection in 2D mammography and C-view

Trovini, G. and Napoli, C. and Marti, R. and Martin, A. and Bria, A. and Marrocco, C. and Molinara, M. and Tortorella, F. and Diaz, Trovini, G., Napoli, C., Marti, R., Martin, A., Bria, A., Marrocco, C., Molinara, M., Tortorella, F., Diaz, O.

Mammogram denoising to improve the calcification detection performance of convolutional nets

Marrocco, C. and Bria, A. and Di Sano, V. and Borges, L.R. and Savelli, B. and Molinara, M. and Mordang, J.-J. and Karssemeijer, N. and Tortorella, Marrocco, C., Bria, A., Di Sano, V., Borges, L. R., Savelli, B., Molinara, M., Mordang, J. -J., Karssemeijer, N., Tortorella, F.

Metrological characterization of a novel microsensor platform for activated carbon filters monitoring

Ferrigno, L., Cerro, G. and Ferdinandi, M. and Ferrigno, L. and Laracca, M. and Molinara, Cerro, G., FERDINANDI, Marco, Laracca, M., Molinara, M.

A Novel Integrated Smart System for Indoor Air Monitoring and Gas Recognition

Bruschi, P. and Cerro, G. and Colace, L. and De Iacovo, A. and Del Cesta, S. and Ferdinandi, M. and Ferrigno, L. and Molinara, M. and Ria, A. and Simmarano, R. and Tortorella, F. and Venettacci, Bruschi, P., Cerro, G., Colace, L., De Iacovo, A., Del Cesta, S., Ferdinandi, M., Ferrigno, L., Molinara, M., Ria, A., Simmarano, R., Tortorella, F., Venettacci, C.

Improving the automated detection of calcifications by combining deep cascades and deep convolutional nets

Bria, A. and Marrocco, C. and Molinara, M. and Savelli, B. and Mordang, J.-J. and Karssemeijer, N. and Tortorella, Bria, A., Marrocco, C., Molinara, M., Savelli, B., Mordang, J. -J., Karssemeijer, N., Tortorella, F.

Improving the Automated Detection of Calcifications using Adaptive Variance Stabilization

Bria, Alessandro, Marrocco, Claudio, Borges, Lucas R., Molinara, Mario, Marchesi, Agnese, Mordang, Jan-Jurre, Karssemeijer, Nico, Tortorella, Francesco

A Sensor Fusion Method Applied to Networked Rain Gauges for Defining Statistically Based Rainfall Thresholds for Landslide Triggering

Leone A., Forleo A., Francioso L., Capone S., Siciliano P., Di Natale C., Fattoruso, Grazia, Agresta, Annalisa, De Vito, Saverio, Buonanno, Antonio, Marrocco, Claudio, Molinara, Mario, Tortorella, Francesco, Di Francia, Girolamo

Preliminary realization of a monitoring system of activated carbon filter RLI based on the SENSIPLUS® microsensor platform

Cerro, G. and Ferdinandi, M. and Ferrigno, L. and Molinara, Cerro, G., Ferdinandi, M., Ferrigno, L., Molinara, M.

Una prima caratterizzazione di un innovativo chip di misura per applicazioni WSN

Associazione Italiana Gruppo di Misure Elettriche ed Elettroniche, M. Ferdinandi, L. Ferrigno, G. Ficco, M. Molinara, R. Simmarano

Illumination Correction by Dehazing for Retinal Vessel Segmentation

P. D. Bamidis, S. Th. Konstantinidis, P. P. Rodrigues, SAVELLI, Benedetta, Bria, Alessandro, Galdran, Adrian, Marrocco, Claudio, Molinara, Mario, Campilho, Aurelio, Tortorella, Francesco

The Effect of Mammogram Preprocessing on Microcalcification Detection with Convolutional Neural Networks

P. D. Bamidis, S. Th. Konstantinidis, P. P. Rodrigues, MARCHESI, Agnese, Bria, Alessandro, Marrocco, Claudio, Molinara, Mario, Mordang, Jan-Jurre, Tortorella, Francesco, Karssemeijer, Nico

Measure for participatory valorization of Cultural Heritage

AA.VV., Cigola M., Gallozzi A., Senatore L. J., Di Maccio R., Molinara M., Trovini G., Marinelli E., Montaquila A., Polito E., De Rosa G.

Online Anomaly Detection on Rain Gauge Networks for Robust Alerting Services to Citizens at Risk from Flooding

orruso G., Cuzzocrea A., Apduhan B.O., Rocha A.M.A.C., Taniar D., Misra S., Gervasi O., Torre C.M., Stankova E., Murgante B., Fattoruso, Grazia, Agresta, Annalista, De Vito, Saverio, Buonanno, Antonio, Molinara, Mario, Marocco, Claudio, Tortorella, Francesco, Di Francia, Girolamo

Spatial Enhancement by Dehazing for Detection of Microcalcifications with Convolutional Nets

Battiato S., Gallo G., Stanco F., Schettini R., BRIA, Alessandro, Marrocco, C., Galdran, A., Campilho, A., Marchesi, A., Mordang, J. J., Karssemeijer, N., Molinara, M., Tortorella, F.

Retinal Vessel Segmentation Through Denoising and Mathematical Morphology

Savelli, Benedetta, Marchesi, Agnese, Bria, Alessandro, Marrocco, Claudio, Molinara, Mario, Tortorella, Francesco

Evaluation and design of a rain gauge network using a statistical optimization method in a severe hydro-geological hazard prone area

Fattoruso, Grazia, Longobardi, Antonia, Pizzuti, Alfredo, Molinara, Mario, Marocco, Claudio, De Vito, Saverio, Tortorella, Francesco, Di Francia, Girolamo

Design of a smart EIS measurement system

Clemente, F. and Romano, M. and Bifulco, P. and Faiella, G. and Molinara, M. and Cesarelli, Clemente, F., Romano, M., Bifulco, P., Faiella, G., Molinara, M., Cesarelli, M.

LUT-QNE: Look-up-table quantum noise equalization in digital mammograms

Lang K., Tingberg A., Timberg P., BRIA, Alessandro, MARROCCO, Claudio, Mordang, J. J., Karssemeijer, N., MOLINARA, Mario, TORTORELLA, Francesco

Deep cascade classifiers to detect clusters of microcalcifications

Lang K., Tingberg A., Timberg P., BRIA, Alessandro, MARROCCO, Claudio, Karssemeijer, N., MOLINARA, Mario, TORTORELLA, Francesco

An effective learning strategy for cascaded object detection

A.Bria, C.Marrocco, M. Molinara, F.Tortorella, INFORMATION SCIENCES, BRIA, Alessandro, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Optimal Sensors Placement for Flood Forecasting Modelling

Bogumil Ulanicki, Zoran Kapelan, Joby Boxall, PROCEDIA ENGINEERING, Fattoruso, Grazia, Agresta, Annalisa, Guarnieri, Guido, Lanza, Bruno, Buonanno, Antonio, MOLINARA, Mario, MARROCCO, Claudio, DE VITO, SAVERIO, TORTORELLA, Francesco, Francia, Girolamo Di

Cascaded Rank-Based Classifiers for Detecting Clusters of Microcalcifications

a cura di Niels Peek, Roque Marín Morales, Mor Peleg, BRIA, Alessandro, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Lecture Notes in Computer Science

Automatic segmentation of the pectoral muscle in mediolateral oblique mammograms

Rodrigues, PP, Pechenizkiy, M, Gama, J, Correia, RC, Liu, J, Traina, A, Lucas, P, Soda, P, MOLINARA, Mario, MARROCCO, Claudio, TORTORELLA, Francesco

A Boosting-Based Approach to Refine the Segmentation of Masses in Mammography

a cura di Alfredo Petrosino, MOLINARA, Mario, MARROCCO, Claudio, TORTORELLA, Francesco

Lecture Notes in Computer Science

A Ranking-based Cascade Approach for Unbalanced Data

nessun autore, BRIA, Alessandro, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Detection of cluster of microcalcifications based on watershed segmentation algorithm

Soda P., Tortorella F., Antani S., Pechenizkiy M., Cannataro M., Tsymbal A., MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco, P. Rinaldi, L. Bonomo, A. Ferrarotti, C. Aragno, S. Schiano lo Moriello

Detecting Clusters of Microcalcifications with a Cascade-Based Approach

a cura di A.D.A. Maidment, P.R. Bakic, and S. Gavenonis, BRIA, Alessandro, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Lecture Notes in Computer Science 7361

A multidisciplinary approach to the design and development of a CAD system for the detection of clustered microcalcifications

T. Solomonides, J. Silverstein, C. McGregor, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco, Rinaldi P., Bonomo L., Ferrarotti A., Aragno C., Schiano lo Moriello S.

On Linear Combinations of Dichotomizers for Maximizing the Area Under the ROC Curve

MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Exploring Cascade Classifiers for Detecting Clusters of Microcalcifications

a cura di G. Maino, G. Foresti, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Lecture Notes on Computer Science 6978

Selection Strategies for pAUC-based Combination of Dichotomizers

a cura di C. Sansone, J. Kittler, F. Roli, RICAMATO, Maria Teresa, MOLINARA, Mario, TORTORELLA, Francesco

Lecture Notes on Computer Science 6713

A Computer-Aided Detection System for Clustered Microcalcifications

ARTIFICIAL INTELLIGENCE IN MEDICINE, MARROCCO, Claudio, MOLINARA, Mario, D'ELIA, Ciro, TORTORELLA, Francesco

Towards a Linear Combination of Dichotomizers by Margin Maximization

a cura di FOGGIA P., SANSONE C., VENTO M., MARROCCO, Claudio, MOLINARA, Mario, RICAMATO, Maria Teresa, TORTORELLA, Francesco

Lecture Notes in Computer Science 5716

Crack Shape Reconstruction in Eddy Current Testing using Machine Learning Systems for Regression

BERNIERI, Andrea, FERRIGNO, Luigi, LARACCA, Marco, MOLINARA, Mario

A Dynamic Programming Approach for Segmenting Digital Planar Curves into Line Segments and Circular Arcs

TORTORELLA, Francesco, PATRACCONE R, MOLINARA, Mario

Detection of Clusters of Microcalcifications in Mammograms: A Multi Classifier Approach

Puuronen S., Pechenizkiy M., Tsymbal A., D'ELIA, Ciro, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Facing imbalanced classes through aggregation of classifiers

MOLINARA, Mario, RICAMATO, Maria Teresa, TORTORELLA, Francesco

An Empirical Comparison of Ideal and Empirical ROC-Based Reject Rules

MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Lecture Notes in Computer Science 4571

An SVM Approach to Crack Shape Reconstruction in Eddy Current Testing

BERNIERI, Andrea, FERRIGNO, Luigi, LARACCA, Marco, MOLINARA, Mario

Exploiting AUC for Optimal Linear Combination of Dichotomizers

PATTERN RECOGNITION LETTERS, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

AUC-Based Linear Combination of Dichotomizers

a cura di D. YEUNG, J.T. KWOK, A. FRED, F. ROLI, D. DE RIDDER, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Lecture Notes in Computer Science 4109

AUC-Based Linear Combination of Dichotomizers

MARROCCO C, MOLINARA, Mario, TORTORELLA F.

SVM-based approach for instrument fault accommodation in automotive systems

IEEE, BERNIERI, Andrea, BETTA, Giovanni, CAPRIGLIONE, Domenico, MOLINARA, Mario

SVM Based Regression Schemes for Instruments Fault Accommodation in Automotive Systems

a cura di F. ROLI, S. VITULANO, CAPRIGLIONE, Domenico, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Lecture Notes in Computer Science 3617

Algorithms for Detecting Clusters of Microcalcifications in Mammograms

a cura di F.Roli, S. Vitulano, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Lecture Notes in Computer Science 3617

Estimating the ROC Curve of Linearly Combined Dichotomizers

a cura di F. ROLI, S. VITULANO, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Lecture Notes in Computer Science 3617

A Multi-Expert System for Movie Segmentation

COLACE F, DE SANTO M, MOLINARA, Mario, PERCANNELLA G, VENTO M.

Comparison of Object-Based Classification Techniques on Multispectral Images

G. CUOZZO, D'ELIA, Ciro, DE STEFANO, Claudio, FONTANELLA, Francesco, C. MARROCCO, MOLINARA, Mario, SCOTTO DI FRECA, Alessandra, F. TORTORELLA

Detection of microcalcification clusters in mammograms through TS MRF segmentation and SVM-based classification

J. Kittler, M. Petrou, M. Nixon, D'ELIA, Ciro, MARROCCO, Claudio, MOLINARA, Mario, G. POGGI, G. SCARPA, TORTORELLA, Francesco

Detection of Microcalcifications Clusters in Mammograms through TS MRF Segmentation and SVM based Classification

C. DELIA, C. MARROCCO, MOLINARA, Mario, G. POGGI, G. SCARPA, F. TORTORELLA

Automatic Classification of Clustered Microcalcifications by a Multiple Expert System

PATTERN RECOGNITION, MOLINARA, Mario, TORTORELLA, Francesco, M. VENTO, M. DE SANTO

MPEG-LAB MOVIE TOOL: AN INTEGRATED AND DISTRIBUTED ENVIRONMENT FOR MPEG VIDEO ANALYSIS

COLACE F, DE SANTO M, MOLINARA, Mario, PERCANNELLA G.

Noisy motion vectors removal for reliable camera parameters estimation in mpeg coded videos

COLACE F, DE SANTO M, MOLINARA, Mario, PERCANNELLA G.

An Automatic Learning Contents Selector Based on Metadata Standards

MOLINARA, Mario, DE SANTO, PERCANNELLA G, COLACE F.

On the applicability of the Multi Agent System Paradigm for Parsing Videos

MOLINARA, Mario, DE SANTO M, PERCANNELLA G.

Multi Agent Systems for Circuit Tolerance and sensitivity analysis

MOLINARA, Mario, DE SANTO M, FEMIA N, SPAGNUOLO G.

Personalized Intelligent Training on The Web: a Multi-Agent Approach

MOLINARA, Mario, CAPUANO N, DE SANTO M, MARSELLA M, SALERNO M. S.