News

The following paper published in Scientific Reports (Nature) discloses some scientific outcomes of the current research:

https://www.nature.com/articles/s41598-018-31479-2

The research activity is the results of a collaboration between the PostDoc Luca Romeo and the Cognition, Motion and Neuroscience and Computational Statistics and Machine Learning Department, Istituto Italiano di Tecnologia, Genova, Italy.

In the mentioned study, the authors applied pattern-classification analyses to kinematic features to verify whether children with autism spectrum disorder (ASD) and typically developing (TD) children altered their initial grasp in anticipation of self- and other-actions.
 

Tra gli altri partecipanti, spetta anche al Prof. Emanuele Frontoni intervenire il 27 settembre a Jesi al primo degli “incontri in Fondazione”.

La web economy, attraverso l’estensione delle piattaforme digitali, già sviluppatesi nel mondo social, porta con sé profondi cambiamenti nelle relazioni tra i differenti attori del processo economico: fornitori, committenti, clienti finali.

Che prospettive hanno in tale contesto le imprese italiane?

Che compito potrà e dovrà svolgere in questo percorso la finanza?

Quali scenari tecnologici costituiscono le principali sfide future del manifatturiero 4.0?

Questi temi saranno affrontati nel corso di una tavola rotonda, a cui si affiancherà l’illustrazione di un’impresa del territorio, Simonetta SpA.

PhD Student Andrea Felicetti attended the Augmented Reality Summer School (AVR) held in Torre dell'Orso (Lecce), Italy on 2-8 September, 2018.

The main aim of the Augmented Reality Summer School has been to propose a moment for stimulating discussions and exchanging scientific experiences and technical results related to this technology.The main thematic areas of the Augmented Reality Summer School has been: medicine, cultural heritage and arts, education, games and serious games.

PhD Student Michele Bernardini attended the Medical Imaging Summer School (MISS) held in Favignana (Italy) on 29 Jul - 04 Aug, 2018. More than 150 participants attended this school.

The focus of this Medical Imaging Summer School was to provide insights into the various interfaces between medical imaging and Deep Learning, based on the shared broad categories of medical image computing, computer-aided image interpretation and disease classification.

The course contained a combination of in-depth tutorial-style lectures on fundamental state-of-the-art concepts, followed by accessible yet advanced research lectures using examples and applications. A broad overview of the field was given, and guided reading groups complemented lectures. The course was delivered by world renowned experts from both academia and industry, who are working closely at the interface of medical imaging/Deep Learning.