Teaching

Machine Learning for Earth Observation powered by Supercomputers
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University of Iceland

Machine Learning for Earth Observation powered by Supercomputers

This course exposes the students to the physical principles underlying satellite observations of Earth by passive sensors, as well as parallel Deep Learning (DL) algorithms that scale on High Performance Computing (HPC) systems.

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Fall Semester 2022

Previous teaching

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS) - Kuala Lumpur, Malaysia

GRSS ESI HDCRS End-to-End Machine Learning with High Performance and Cloud Computing

17 July, 2022
Università degli Studi del Sannio di Benevento

Artificial Intelligence for Earth Observation powered by High Performance Computing and Quantum Computing

2021
IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

Scalable Machine Learning with High Performance and Cloud Computing

July 10-11, 2021
University of Bonn

Parallel and Scalable Machine Learning for Remote Sensing Big Data

WS 2020-2021
University of Iceland

Deep Learning driven by Big Data

20/10/2020
TU Berlin

Image Filtering with Mathematical Morphology Operators

May 2020
University of Bonn

Parallel and Scalable Machine Learning for Remote Sensing Big Data

WS 2019-2020
Jülich Supercomputing Centre

PRACE Tutorial Parallel and Scalable Machine Learning

February 2020
IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

Scalable Machine Learning with High Performance and Cloud Computing

26-27/09/2020

Prof. Gabriele Cavallaro © 2022  |  All Rights Reserved.

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