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InterPARES Trust AI meeting @ Rome

Prof. Emanuele Frontoni attended at Interpares Trust AI global meeting in Rome.

The project aims to support the ongoing availability and accessibility of trustworthy public records by forming a sustainable, ongoing partnership producing original research, training students and other highly qualified personnel, and generating a virtuous circle between academia, archival institutions, government records professionals, and industry.

More info at https://interparestrustai.org/trust

Machine Learning based decision support system for early-stage prediction of complications and risk stratification of COVID 19 patients @ IEEE EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH 2021

IEEE EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH 2021
WS: Machine Learning based decision support system for early-stage prediction of complications and risk stratification of COVID 19 patients

Unlocking the potential of Artificial Intelligence for UltraSound image processing @ IEEE EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH 2021

IEEE EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH 2021

WS: AI4US: Unlocking the potential of Artificial Intelligence for UltraSound image processing

Organisers: Sara Moccia, PhD - The BioRobotics Institute, Scuola Superiore Sant’Anna and Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, Pisa, Italy – sara.moccia@santannapisa.it

Call for paper - Designing Machine Learning approaches for early-stage prediction of complications and risk stratification of COVID-19 patients

 

The Journal of Medical & Biological Engineering & Computing is now accepting submissions to an upcoming special issue, entitled:

Designing Machine Learning approaches for early-stage prediction of complications and risk stratification of COVID-19 patients

The Guest Editors board is represented also by Luca Romeo, Michele Bernardini, and Emanuele Frontoni of the VRAI Lab.

For further info and deadlines:

VRAI XMAS 2020

https://youtu.be/YEuQDq3km3E

Warmest wishes for a wonderful Christmas and a better New Year from the UNIVPM VRAI Lab to all our members, students, partners and followers. GAN-fashion neural networks learned how to generate Christmas tree images, trained over 1K epochs with about 1K images per epoch. The dataset contains about 2k images of Christmas trees, augmented to about 10K images.

Code & credits: https://github.com/aleju/christmas-generator

La scienza al femminile

 

Anche il dipartimento di ingegneria dell'informazione dell' Università Politecnica delle Marche sarà presente alla notte Europea dei ricercatori.
Veronica (del LabMACS) e Lucia (del VRAI), faranno due interventi sulle loro attività di ricerca: la robotica sottomarina e l'intelligenza artificiale per l'analisi di immagini mediche. 

Link per vedere l'intervento: https://mondodigitale.org/sites/default/files/veronica_bartolucci_lucia_...

Nuovo ponte di Genova: Sistema robotico di ispezione visuale automatica

 

Il 12 Novembre è stato presentato il sistema robotico di ispezione visuale automatica installato nel nuovo ponte di Genova. Le Marche hanno contribuito alla realizzazione della più importante infrastruttura tecnologica al mondo di ispezione di una grande e cruciale infrastruttura viaria.

Adriano Mancini ed Emanuele Frontoni del gruppo VRAI, in collaborazione con UBISIVE, si sono occupati di sviluppare la parte dei sistemi di visione dei robot.

Alla conferenza di presentazione hanno partecipato:

- Gian Luca Gregori - Rettore UNIVPM 

AI for Health @ Microsoft

VRAI Lab is happy to share that our Information Engineering Department (DII) at Università Politecnica delle Marche was granted by Microsoft AI for Health COVID-19 programme with our project aiCOVID19!
We try to join our forces with international researchers worldwide to combat the new coronavirus epidemic and to understand its aftermath. 

Info on the Microsoft AI for Health project: https://www.microsoft.com/en-us/ai/ai-for-health

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