Skip links
grssvector240
iadfvector
GRSS & IADF

IADF SCHOOL

Computer Vision for Earth Observation
Monday, October 3 – Friday, October 7, 2022
9+ Topics
17+ Lectures
9+ Theoretical sessions
9+ Hands-on (lab) sessions
Apply

IEEE Geoscience and Remote Sensing Society

First IADF School on 

Computer Vision for Earth Observation

ONLINE SCHOOL

Monday, October 3 – Friday, October 7, 2022.

08:00 – 16:00 UTC 

10:00 – 18:00 CEST (UTC + 2)

16:00 – 24:00 China Standard Time (UTC + 8)

04:00 – 12:00 Eastern Daylight Time (UTC – 5)

The last few years have seen an increase in the number of earth observation platforms, such as satellites and airborne sensors which can monitor the earth’s surface. The availability of a wide range of sensors from optical, hyperspectral to synthetic aperture radar further facilitates a more accurate observation of earth surface. The images acquired from these sensors are typically analyzed using computer vision methods such as segmentation, classification, registration, detection, fusion, regression, etc.

 

As the IEEE GRSS IADF, we are pleased to announce our first school on Computer Vision for Earth Observation (CV4EO). This school will focus on applying CV methods to address challenges in remote sensing. This school will contain a series of lectures on the existing methods utilized for analyzing satellite images, along with the challenges encountered. Each lecture (2h) will be followed by a practical session (2h) where the participants will implement the techniques discussed in the lecture using some commonly used programming languages (e.g., Python) and open-source software tools to address the exercises provided by the expert teachers. The school will be held online from October 3-7, 2022. 

 

The school is open to everybody who has a strong motivation and interest in the topics addressed by it. Participants will not be charged a registration fee. The number of participants is limited to 75 to guarantee high-quality lessons with good interaction. If a higher number of registrations is received, the organizing committee will select the 75 participants and the broadcasting of the course will be guaranteed to everyone who showed an interest. All the selected participants will receive a certificate confirming their attendance to the school.

Covered Topics

  1. Image Fusion 
  2. Explainable AI for the Earth Science
  3. Big Geo-Data
  4. Multi-source Image Analysis
  5. Deep Learning for Spectral Unmixing 
  6. SAR Image Analysis 
  7. Learning with Zero/Few Labels

Contact email : gemine.vivone@imaa.cnr.it

Technical Program

Topics

Speakers

Affiliations

OCTOBER 3

10:00-14:00 (UTC +2)

Deep/Machine Learning for Spectral Unmixing

Helmholtz-Zentrum Dresden-Rossendorf (Germany)

14:00-18:00 (UTC +2)

Change Detection (TorchGeo)

Microsoft (USA)

OCTOBER 4

10:00-14:00 (UTC +2)

Learning with Zero/Few Labels

Technical University of Munich (Germany), German Aerospace Center (Germany), University of Cambridge (UK)

14:00-18:00 (UTC +2)

SAR Processing

IIRS, ISRO (India)

OCTOBER 5

10:00-14:00 (UTC +2)

Semantic Segmentation

Universitè de Paris (France)

14:00-18:00 (UTC +2)

Big Geo-Data

University of Houston (USA), Purdue University (USA)

OCTOBER 6

10:00-14:00 (UTC +2)

Image Fusion

University of Naples “Federico II” (Italy)

14:00-18:00 (UTC +2)

XAI for Earth Science

University of Valencia (Spain)

OCTOBER 7

09:00-13:00 (UTC +2)

PolSAR

Indian Unstitute of Technology Bombay (India), Victoria University of Wellington (New Zealand), Kansas State University (USA)

Organizing Committee

Gemine Vivone

National Research Council, Italy

gemine.vivone@imaa.cnr.it

Ronny Hänsch

German Aerospace Center, Germany

rww.haensch@gmail.com

Claudio Persello

University of Twente, The Netherlands

c.persello@utwente.nl

Dalton Lunga

Oak Ridge National Laboratory, USA

lungadd@ornl.gov

Gülşen Taşkın

Istanbul Technical University, Turkey

gulsen.taskin@itu.edu.tr

Ujjwal Verma

Manipal Institute of Technology, India

ujjwal.verma@manipal.edu

Francescopaolo Sica

German Aerospace Center, Germany

fr.sica@gmail.com

Srija Chakraborty

NASA GSFC, USRA, USA

srijac0530@gmail.com

Speakers

Prof. Melba Crawford

Big Geo-Data

Purdue University (USA)

Prof. Saurabh Prasad

Big Geo-Data

University of Houston (USA)

Dr. Caleb Robinson

Change Detection

Microsoft (USA)

Dr. Behnood Rasti

Deep/Machine Learning for Spectral Unmixing

Helmholtz-Zentrum Dresden-Rossendorf (Germany)

Dr. Matteo Ciotola

Image Fusion

University of Naples “Federica II” (Italy)

Prof. Giuseppe Scarpa

Image Fusion

University of Naples “Federica II” (Italy)

Dr. Sudipan Saha

Learning with Zero Few Labels

Technical University of Munich (Germany)

Dr. Angelica I. Aviles-Rivero

Learning with Zero Few Labels

University of Cambridge (UK)

Dr. Lichao Mou

Learning with Zero Few Labels

German Aerospace Center (Germany)

Prof. Carola-Bibiane Schönlieb

Learning with Zero Few Labels

University of Cambridge (UK)

Prof. Xiao Xiang Zhu

Learning with Zero Few Labels

Technical University of Munich (Germany)

Prof. Avik Bhattacharya

PolSAR

Indian Unstitute of Technology Bombay (India)

Prof. Alejandro Frery

PolSAR

Victoria University of Wellington (New Zealand)

Dr. Dipankar Mandal

PolSAR

Kansas State University (USA)

Dr. Shashi Kumar

SAR Processing

IIRS, ISRO (India)

Prof. Sylvain Lobry

Semantic Segmentation

Universitè de Paris (France)

Dr. Michele Ronco

XAI

University of Valencia (Spain)