Signal Processing – Signal Processing Meets Deep Learning

About

The 2017 IEEE Summer School on Signal Processing (S3P-2017), organized by the IEEE Signal Processing Society Italy Chapter, represents a stimulating environment where top international scientists in signal processing and related disciplines share their ideas on fundamental and ground-breaking methodologies in the field. It provides PhD students and researcher with a unique networking opportunity and possibility of interaction with leading scientists.

The theme of this 5th edition is "Signal Processing meets Deep Learning". Deep machine learning is changing the rules in the signal and multimedia processing field. On the other hand, signal processing methods and tools are fundamental for machine learning. Time for these worlds to meet.

This year lecturers are characterized by very diverse background, from signal and image processing, to computer vision and machine learning:

Mauro Barni (University of Siena, I)
Michael Elad (Technion, IL)
Iasonas Kokkinos (Facebook Artificial Intelligence Research and University College London, UK)
Stephane Mallat (Ecole Normale Superieure, F)
Peyman Milanfar (Google Research, USA)
Hermann Ney (Aachen University, D)
Fabio Roli (University of Cagliari, I)
Silvio Savarese (Stanford University, USA)
Andrea Vedaldi (Oxford University, UK)

Lectures will cover both theoretical and applicative topics, with special emphasis on seeing and understanding deep learning from a signal processing perspective. In addition, the School will give the students the opportunity to present their work and to interact with the teachers about their current and future research. A test will be performed during the last day to obtain a certificate worth ECTS credits.

Course leader

Mauro Barni (University of Siena, I) Michael Elad (Technion, IL) Iasonas Kokkinos (Facebook Artificial Intelligence Research and University College London, UK) Stephane Mallat (Ecole Normale Superieure, F) Peyman Milanfar (Google Resea

Target group

Phd students, researchers, MS student, Industries

Fee info