4th Earth Observation Applications Summer School (Uydu Yer Gözlem Uygulamaları Yaz Okulu - UYGU2021)
4th Earth Observation Applications Summer School - UYGU2021
On behalf of the IEEE Geoscience and Remote Sensing Society (GRSS) Turkey Chapter, we are pleased to invite you to the 4th Earth Observations Applications Summer School, UYGU2021, which will be held from August 30 to September 2, 2021, in a virtual environment.
UYGU2021 is organized by the IEEE GRSS Turkey Chapter, with the support of GRSS Benelux and GRSS Switzerland Chapters, and with the sponsorship of IEEE GRSS. The theme for UYGU2021 is set as "Deep Learning for Remote Sensing".
Deep learning presents promising opportunities to meet the challenges of remote sensing, and UYGU2021 seeks to highlight the latest developments and trends in the used of deep learning for remote sensing related studies. Deep learning for feature extraction, classification of hyperspectral images, SAR data analysis, fusion, and multitemporal and multisource data analysis are some of the topics that will be covered in the summer school. The organizers anticipate a technically outstanding summer school, with the carefully formed technical program and the exceptional invited lecturers. UYGU2021 is primarily aimed at graduate students, faculty staff, and researchers who wish to stay current on recent discoveries and future trends on deep learning topics dealing with remote sensing. However, there are no prerequisites for attendance. The summer school is free of charge and open to all interested participants who register.
Registration is now open. Please visit the UYGU2021 website https://grssturkey.org/en/uygu2021 for more details and do not hesitate to broadcast this information around you.
We look forward to meeting you during UYGU2021,
UYGU2021 Organization Commitee
Date and Time
Location
Hosts
Registration
- Start time: 30 Aug 2021 08:30 AM
- End time: 02 Sep 2021 04:30 PM
- All times are (GMT+01:00) CET
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uygu2021@gmail.com
- Co-sponsored by IEEE GRSS
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Speakers
Berrin Yanıkoğlu of Sabancı University, Turkey
CNN for Image Understanding
Biography:
Berrin Yanikoglu received a double major in Computer Science and Mathematics from Bogazici University in 1988 and her Ph.D. degree in Computer Science from Dartmouth College, USA in 1993. After a year as a post-doctoral associate at Rockefeller University, she worked at Xerox Imaging Systems and IBM Almaden Research Center on document image understanding problems and has received an IBM Research Award in 1998. Prof. Yanikoglu joined Sabanci University in 2000 as a faculty member, where she has been teaching since, and is serving as the Director of the Sabanci University Center of Excellence in Data Analytics (VERIM) since its foundation in 2016. Prof. Yanikoglu`s research interests lie in machine learning with applications to image/video understanding; and biometric verification and biometric privacy. She and her students have received first-place positions in multiple image understanding and biometric verification competitions worldwide.
Behnood Rasti of Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Germany
Deep Feature Extraction and Classification for Hyperspectral Imagery
Biography:
Behnood Rasti (Senior Member, IEEE) received the B.Sc. and M.Sc. degrees both in electronics-electrical engineering from the Electrical Engineering Department, University of Guilan, Rasht, Iran, in 2006 and 2009, respectively, and the Ph.D. degree in electrical and computer engineering from the University of Iceland, Reykjavik, Iceland, in 2014. In 2015 and 2016, he worked as a Post-Doctoral Researcher and a Seasonal Lecturer with the Electrical and Computer Engineering Department, University of Iceland. From 2016 to 2019, he has been a Lecturer with the Center of Engineering Technology and Applied Sciences, Department of Electrical and Computer Engineering, University of Iceland. His research interests include signal and image processing, machine/deep learning, remote sensing image fusion, hyperspectral feature extraction and classification, spectral unmixing, remote sensing image denoising, and restoration. Dr. Rasti won the prestigious “Alexander von Humboldt Research Fellowship Grant” in 2019 and started his work in 2020 as a Humboldt Research Fellow with Machine Learning Group, Helmholtz-Zentrum DresdenRossendorf (HZDR), Freiberg, Germany. He was the Valedictorian as an M.Sc. Student in 2009 and he won the Doctoral Grant of The University of Iceland Research Fund and was awarded “The Eimskip University fund,” in 2013. He serves as an Associate Editor for the IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (GRSL) and Remote Sensing (Multidisciplinary Digital Publishing Institute).
Agenda
IEEE GRSS Turkey Chapter is pleased to invite you to the Fourth Earth Observation Applications Summer School, UYGU2021, with the theme “Deep Learning for Remote Sensing”.
UYGU2021 will be hosted in a virtual environment between the dates of August 30 – September 2, 2021. UYGU2021 is organized by the IEEE GRSS Turkey Chapter, with the support of IEEE GRSS Benelux and IEEE GRSS Switzerland Chapters, and with the sponsorship of IEEE GRSS under the ChapNet program.
In the four day summer school, experts in their fields will give lectures on the topics given below.
Deep feature extraction and classification for hyperspectral imagery
Deep mining and fusion for image interpretation in remote sensing
Deep learning: From remotely sensed data to geo-spatial semantic information
Multitemporal, multisource and mulltiscale remote sensing in the era of deep learning
Deep Learning in Remote Sensing: Good Practices and Solutions for Complex Data
Deep Learning for SAR Processing and Analysis
We wish you a productive summer school experience.
IEEE GRSS Turkey Chapter
Media
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