2025
Software
Open Access
Named entity recognition with BERT
Esuli A.
Two scripts for training and testing BERT-like pretrained models on Named Entity Recognition (NER) tasks. Train (finetune) a BERT-based NER model (from Hugging Face or a model stored on your computer) on a dataset formatted in CoNLL-like format. Use the trained model to predict NER tags on test data, getting an evaluation report, or new data, getting a tagged version the data. The scripts handle sequences longer than the maximum length defined by the models by splitting the sequences in multiple chunks with a context overlap.DOI: 10.5281/zenodo.14760697
Project(s): Future Artificial Intelligence Research, Italian Strengthening of the ESFRI RI RESILIENCE, SoBigData.it
Metrics:
Esuli A.
Two scripts for training and testing BERT-like pretrained models on Named Entity Recognition (NER) tasks. Train (finetune) a BERT-based NER model (from Hugging Face or a model stored on your computer) on a dataset formatted in CoNLL-like format. Use the trained model to predict NER tags on test data, getting an evaluation report, or new data, getting a tagged version the data. The scripts handle sequences longer than the maximum length defined by the models by splitting the sequences in multiple chunks with a context overlap.DOI: 10.5281/zenodo.14760697
Project(s): Future Artificial Intelligence Research, Italian Strengthening of the ESFRI RI RESILIENCE, SoBigData.it
Metrics:
See at:
github.com 
| CNR IRIS | CNR IRIS 
2024
Software
Restricted
TagLab 2024.12.2
Corsini M., Pavoni G., Ponchio F., Muntoni A., Saraceni Q., Cignoni P.
TagLab is an AI-powered segmentation software designed to support the analysis of large orthographic images generated through the photogrammetric pipeline.DOI: 10.5281/zenodo.14258304
Metrics:
Corsini M., Pavoni G., Ponchio F., Muntoni A., Saraceni Q., Cignoni P.
TagLab is an AI-powered segmentation software designed to support the analysis of large orthographic images generated through the photogrammetric pipeline.DOI: 10.5281/zenodo.14258304
Metrics:
See at:
CNR IRIS | CNR IRIS | taglab.isti.cnr.it
2024
Software
Open Access
OAI-PMH Server v1.0.0
Artini M.
A SpringBoot application that permits to export metadata records according to the OAI-PMH protocol. This version is based on a Postgres Database. This is the first release of the application.DOI: 10.5281/zenodo.13938870
Project(s): EOSC Beyond
Metrics:
Artini M.
A SpringBoot application that permits to export metadata records according to the OAI-PMH protocol. This version is based on a Postgres Database. This is the first release of the application.DOI: 10.5281/zenodo.13938870
Project(s): EOSC Beyond
Metrics:
See at:
github.com | CNR IRIS | CNR IRIS
2024
Software
Open Access
RelightLab 2024.11
Ponchio F., Potenziani M., Muntoni A., Cignoni P.
Relight is a library to create and view (on the web) relightable images (RTI), It supports Polinomial Texture Mapping (PTM), Hemispherical Harmonics (HSH) along with a new Principal Component Analysis (PCA) + Radial Basis Function (RBF) based algorithm with better fidelity (for the same cost and space). It also supports RTI (and image) streamed tiled viewing based on DeepZoom, Google, Zoomify, IIP formats.DOI: 10.5281/zenodo.14196912
Metrics:
Ponchio F., Potenziani M., Muntoni A., Cignoni P.
Relight is a library to create and view (on the web) relightable images (RTI), It supports Polinomial Texture Mapping (PTM), Hemispherical Harmonics (HSH) along with a new Principal Component Analysis (PCA) + Radial Basis Function (RBF) based algorithm with better fidelity (for the same cost and space). It also supports RTI (and image) streamed tiled viewing based on DeepZoom, Google, Zoomify, IIP formats.DOI: 10.5281/zenodo.14196912
Metrics:
See at:
CNR IRIS | vcg.isti.cnr.it | CNR IRIS
2024
Software
Open Access
PyMeshLab 2023.12.post2
Muntoni A., Cignoni P.
PyMeshLab is a Python library that interfaces to MeshLab, the popular open source application for editing and processing large 3D triangle meshes. Python bindings are generated using pybind11.DOI: 10.5281/zenodo.13768931
Metrics:
Muntoni A., Cignoni P.
PyMeshLab is a Python library that interfaces to MeshLab, the popular open source application for editing and processing large 3D triangle meshes. Python bindings are generated using pybind11.DOI: 10.5281/zenodo.13768931
Metrics:
See at:
CNR IRIS | pymeshlab.readthedocs.io | CNR IRIS
2023
Software
Metadata Only Access
Experimenting with formal verification and model-based development in railways: the case of UMC and Sparx Enterprise Architect - Complementary data
Basile D, Mazzanti F, Ferrari A
This repository contains the UMC and SPARX EA data used in the paper: Experimenting with Formal Verification and Model-based Development in Railways: the case of UMC and Sparx Enterprise Architect by Davide Basile, Franco Mazzanti and Alessio Ferrari.DOI: 10.5281/zenodo.7920448
Project(s): 4SECURAIL
Metrics:
Basile D, Mazzanti F, Ferrari A
This repository contains the UMC and SPARX EA data used in the paper: Experimenting with Formal Verification and Model-based Development in Railways: the case of UMC and Sparx Enterprise Architect by Davide Basile, Franco Mazzanti and Alessio Ferrari.DOI: 10.5281/zenodo.7920448
Project(s): 4SECURAIL
Metrics:
See at:
CNR IRIS
2023
Software
Metadata Only Access
A toolchain for strategy synthesis with spatial properties - Complementary material
Basile D, Ter Beek Mh, Bussi L, Ciancia V
This is the complementary material for our paper ``A Toolchain for Strategy Synthesis with Spatial Properties'' accepted for publication at the Journal of Software Tools and Technology Transfer. This repository contains a permanent snapshot of https://github.com/contractautomataproject/CATLib_PngConverter/tree/ec0938043146b008bbbcb4ed3ec79c06dd2e47d6DOI: 10.5281/zenodo.8220527
Metrics:
Basile D, Ter Beek Mh, Bussi L, Ciancia V
This is the complementary material for our paper ``A Toolchain for Strategy Synthesis with Spatial Properties'' accepted for publication at the Journal of Software Tools and Technology Transfer. This repository contains a permanent snapshot of https://github.com/contractautomataproject/CATLib_PngConverter/tree/ec0938043146b008bbbcb4ed3ec79c06dd2e47d6DOI: 10.5281/zenodo.8220527
Metrics:
See at:
CNR IRIS
2023
Software
Metadata Only Access
MEC: Mesoscale Events Classifier
Papini O
This software consists of a Python 3 implementation of the Mesoscale Events Classifier (MEC) algorithm, which has been developed as part of the activities of Task 8.5 of the NAUTILOS project. The algorithm uses Sea Surface Temperature data coming from satellite missions to detect and classify patterns associated with "mesoscale events" in an upwelling ecosystem.Project(s): NAUTILOS
Papini O
This software consists of a Python 3 implementation of the Mesoscale Events Classifier (MEC) algorithm, which has been developed as part of the activities of Task 8.5 of the NAUTILOS project. The algorithm uses Sea Surface Temperature data coming from satellite missions to detect and classify patterns associated with "mesoscale events" in an upwelling ecosystem.Project(s): NAUTILOS
See at:
github.com | CNR IRIS
2023
Software
Open Access
Modelling, verifying and testing the contract automata runtime environment with Uppaal: complementary data
Basile D
This repository contains the complementary material for the paper: "Modelling and Verifying the Contract Automata Runtime Environment", Basile D. The latest version of the included files can be accessed through the GitHub repository of the Contract Automata Runtime Environment, https://github.com/contractautomataproject/CARE/tree/master/src/spec/uppaal In addition to the other contents, this Zenodo repository contains all the logs of the experiments.
Basile D
This repository contains the complementary material for the paper: "Modelling and Verifying the Contract Automata Runtime Environment", Basile D. The latest version of the included files can be accessed through the GitHub repository of the Contract Automata Runtime Environment, https://github.com/contractautomataproject/CARE/tree/master/src/spec/uppaal In addition to the other contents, this Zenodo repository contains all the logs of the experiments.
See at:
CNR IRIS | zenodo.org | CNR IRIS
2023
Software
Metadata Only Access
Robot personalities module
Zedda E
Description: An application designed to enhance cognitive stimulation among older adults by manipulating robot behaviours into a cooking game. The application incorporates a personality module that generates two robot personalities (extravert and introvert) designed and implemented to improve the Human-Robot Interaction (HRI) of older adults with cognitive impairments. Technologies used: Java, QiSDK, SQL Version: 5.0 CNR Link: https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/Personality
Zedda E
Description: An application designed to enhance cognitive stimulation among older adults by manipulating robot behaviours into a cooking game. The application incorporates a personality module that generates two robot personalities (extravert and introvert) designed and implemented to improve the Human-Robot Interaction (HRI) of older adults with cognitive impairments. Technologies used: Java, QiSDK, SQL Version: 5.0 CNR Link: https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/Personality
See at:
CNR IRIS
2023
Software
Metadata Only Access
Robot personalities adaptation system
Zedda E
Description: An application with an adaptation technique implemented on a humanoid robot to make it autonomously adapt its behaviour during user interaction. The application read the user's state (smile value and gaze direction), classified the engagement level following a defined classification and adapted its behaviours using a Q-learning algorithm (Reinforcement Learning algorithm) performing different robot movements and dialogues according to the user state detected and robot personality chosen. The adaption system is applied at a difficult level of a cooking serious game. Technologies used: Java, QiSDK, SQL, Python CNR Link: https://gitea-s2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/MediumAdaptation
Zedda E
Description: An application with an adaptation technique implemented on a humanoid robot to make it autonomously adapt its behaviour during user interaction. The application read the user's state (smile value and gaze direction), classified the engagement level following a defined classification and adapted its behaviours using a Q-learning algorithm (Reinforcement Learning algorithm) performing different robot movements and dialogues according to the user state detected and robot personality chosen. The adaption system is applied at a difficult level of a cooking serious game. Technologies used: Java, QiSDK, SQL, Python CNR Link: https://gitea-s2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/MediumAdaptation
See at:
CNR IRIS
2023
Software
Metadata Only Access
Match-mismatch user/robot personality
Zedda E
An application that autonomously adapts the robot's personality based on the user personality test results, displaying a robot personality that aligns better with the user's traits in a cooking serious game for older adults with cognitive impairments. Technologies used: Java, QiSDK, SQL
Zedda E
An application that autonomously adapts the robot's personality based on the user personality test results, displaying a robot personality that aligns better with the user's traits in a cooking serious game for older adults with cognitive impairments. Technologies used: Java, QiSDK, SQL
See at:
CNR IRIS
2023
Software
Metadata Only Access
DialogFlow, Google speech API and ChatGPT4 on Pepper
Zedda E, Manca M
Integration of DialogFlow and Google Speech API on a HRI application for Pepper robot. Technologies used: Java, QiSDK, SQL, Google Speech API, DialogFlow API, Azure and OpenAI API CNR Link: https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/DialogFlow_Pepper https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/GoogleSpeechAPI https://gitea-s2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/ChatGPTAzure
Zedda E, Manca M
Integration of DialogFlow and Google Speech API on a HRI application for Pepper robot. Technologies used: Java, QiSDK, SQL, Google Speech API, DialogFlow API, Azure and OpenAI API CNR Link: https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/DialogFlow_Pepper https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/GoogleSpeechAPI https://gitea-s2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/ChatGPTAzure
See at:
CNR IRIS
2023
Software
Metadata Only Access
Q-Learning algorithm for robot behaviour adaptation
Zedda E
An application that applies the Q-learning algorithm to support an adaptation strategy for the robot in the context of an application for cognitive training. The goal is to help the user maintain a high-engaged level and stimulate in case the user is at a low-engaged level. In the project, the robot agent learns its policy by leveraging the simulator by interacting with the simulated users, updating its knowledge using the Bellman Equation. The algorithm returns a trained Q matrix(s, a). Programming Language: Python
Zedda E
An application that applies the Q-learning algorithm to support an adaptation strategy for the robot in the context of an application for cognitive training. The goal is to help the user maintain a high-engaged level and stimulate in case the user is at a low-engaged level. In the project, the robot agent learns its policy by leveraging the simulator by interacting with the simulated users, updating its knowledge using the Bellman Equation. The algorithm returns a trained Q matrix(s, a). Programming Language: Python
See at:
CNR IRIS
2023
Software
Metadata Only Access
VAE for dummies
Martino G
Semplice implementazione di un Variational Autoencoder (VAE) in Pytorch Lightning con un applicativo interattivo ausiliario per esplorare in tempo reale lo spazio latente del VAE.
Martino G
Semplice implementazione di un Variational Autoencoder (VAE) in Pytorch Lightning con un applicativo interattivo ausiliario per esplorare in tempo reale lo spazio latente del VAE.
See at:
github.com | CNR IRIS
2023
Software
Metadata Only Access
Image segmentation tool
Martino G
Software sviluppato in Python con GUI che permette la creazione di dataset per la segmentazione di immagini e l'esportazione in formato COCO.
Martino G
Software sviluppato in Python con GUI che permette la creazione di dataset per la segmentazione di immagini e l'esportazione in formato COCO.
See at:
github.com | CNR IRIS
2022
Software
Metadata Only Access
Concern - COmplex eveNt proCEssing monitoR iNfrastructure
Calabrò A.
Concern is a predictive simulation monitoring infrastructure that aims to cooperate within Digital Twin in execution on a simulated environment to avoid possible accidents or failures happen in real systems using forecasting and self-generation rules techniques.Project(s): BIECO
Calabrò A.
Concern is a predictive simulation monitoring infrastructure that aims to cooperate within Digital Twin in execution on a simulated environment to avoid possible accidents or failures happen in real systems using forecasting and self-generation rules techniques.Project(s): BIECO
See at:
github.com | CNR IRIS
2022
Software
Metadata Only Access
Contract automata runtime environment (v.1.0.0 - February 2022)
Basile D
This document links the zenodo repository of CARE. Contract Automata Runtime Environment (v. February 2022) CARE is a library for implementing applications specified via contract automata. CARE provides a runtime environment to coordinate the CARE services that are implementing the contracts of the synthesised orchestration. Thus, CARE is the missing piece between specifications through contract automata and their implementations, so making explicit the low-level interactions realising the prescribed actions.DOI: 10.5281/zenodo.6393314
Metrics:
Basile D
This document links the zenodo repository of CARE. Contract Automata Runtime Environment (v. February 2022) CARE is a library for implementing applications specified via contract automata. CARE provides a runtime environment to coordinate the CARE services that are implementing the contracts of the synthesised orchestration. Thus, CARE is the missing piece between specifications through contract automata and their implementations, so making explicit the low-level interactions realising the prescribed actions.DOI: 10.5281/zenodo.6393314
Metrics:
See at:
CNR IRIS
2022
Software
Restricted
Multivariate time series dataset generator
Belli D, Miori V
Una classe Java che fornisce i costruttori e i metodi per generare data set sintetici di serie temporali multi-variate con o senza anomalie. La classe Random è usata per aggiungere la giusta percentuale di aleatorietà alla generazione dei segnali che compongono il data set. Gli schemi temporali sono stati modellati in base a funzioni trigonometriche (i.e., seno e coseno), selezionate casualmente da caratteristica a caratteristica. Per riprodurre le anomalie, viene aggiunto un po' di rumore ai segnali generati. La classe è stata pensata per testare algoritmi di apprendimento automatico sviluppati per l'individuazione di anomalie in serie temporali multi-variate.
Belli D, Miori V
Una classe Java che fornisce i costruttori e i metodi per generare data set sintetici di serie temporali multi-variate con o senza anomalie. La classe Random è usata per aggiungere la giusta percentuale di aleatorietà alla generazione dei segnali che compongono il data set. Gli schemi temporali sono stati modellati in base a funzioni trigonometriche (i.e., seno e coseno), selezionate casualmente da caratteristica a caratteristica. Per riprodurre le anomalie, viene aggiunto un po' di rumore ai segnali generati. La classe è stata pensata per testare algoritmi di apprendimento automatico sviluppati per l'individuazione di anomalie in serie temporali multi-variate.
See at:
github.com | CNR IRIS | CNR IRIS
2022
Software
Metadata Only Access
Story Map Building and Visualising Tool (SMBVT)
Lenzi E., Bartalesi Lenzi V., Pratelli N., Coro G., Pagano P.
In the context of the MOVING (MOuntain Valorisation through INterconnectedness and Green growth) project, we released an open-source software - the MOVING Story Map Building and Visualization Tool (SMBVT) - that allows users to create and visualise story maps within a collaborative environment and using a user-friendly Web interface. The tool uses Semantic Web technologies and the Narrative Ontology to represent the stories of the MOVING mountain Value Chains. The MOVING community access SMBVT through The MOVING story map Virtual Research Environment and creates the events of the story. For each event, the user can add: a title, a textual description, start and end dates, the geographic coordinates, a media object (i.e. a video or image), notes, and digital objects. The tool takes Wikidata as reference KB and assigns Wikidata Internationalized Resource Identifiers (IRIs) to the story components (i.e. the entities that take part in an event). All the knowledge collected by SMBVT is stored in a JSON Postgres DB. When a story is completed, the tool automatically creates the corresponding visualisation using StoryMapJS library and makes available a corresponding URL that can be freely shared. Finally, SMBVT saves the collected knowledge as a Web Ontology Language (OWL) graph and publishes it as a Linked Open Data.Project(s): "CMG Collaborative Research": A Systematic Approach to Large Amplitude Internal Wave Dynamics: An Integrated Mathematical, Observational, and Remote Sensing Model, Blue Cloud, MOVING
Lenzi E., Bartalesi Lenzi V., Pratelli N., Coro G., Pagano P.
In the context of the MOVING (MOuntain Valorisation through INterconnectedness and Green growth) project, we released an open-source software - the MOVING Story Map Building and Visualization Tool (SMBVT) - that allows users to create and visualise story maps within a collaborative environment and using a user-friendly Web interface. The tool uses Semantic Web technologies and the Narrative Ontology to represent the stories of the MOVING mountain Value Chains. The MOVING community access SMBVT through The MOVING story map Virtual Research Environment and creates the events of the story. For each event, the user can add: a title, a textual description, start and end dates, the geographic coordinates, a media object (i.e. a video or image), notes, and digital objects. The tool takes Wikidata as reference KB and assigns Wikidata Internationalized Resource Identifiers (IRIs) to the story components (i.e. the entities that take part in an event). All the knowledge collected by SMBVT is stored in a JSON Postgres DB. When a story is completed, the tool automatically creates the corresponding visualisation using StoryMapJS library and makes available a corresponding URL that can be freely shared. Finally, SMBVT saves the collected knowledge as a Web Ontology Language (OWL) graph and publishes it as a Linked Open Data.Project(s): "CMG Collaborative Research": A Systematic Approach to Large Amplitude Internal Wave Dynamics: An Integrated Mathematical, Observational, and Remote Sensing Model, Blue Cloud
, MOVING
See at:
github.com | CNR IRIS