Slide Fifth
Slide Second
Slide Fourth
Slide Sixth
Slide Sixth
International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

TH4.O-4.3

Comparing area-based and feature-based methods for co-registration of multispectral bands on GPU

Álvaro Ordóñez, Dora B. Heras, Francisco Argüello, Universidade de Santiago de Compostela, Spain
Session:
Data Intensive Computing for Remote Sensing
Track:
Invited Sessions
Presentation Time:
Thu, 15 Jul, 15:10-15:25 (UTC)
Thu, 15 Jul, 17:10-17:25 Central Europe Summer Time (UTC +2)
Thu, 15 Jul, 23:10-23:25 China Standard Time (UTC +8)
Thu, 15 Jul, 11:10-11:25 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Gabriele Cavallaro, Forschungszentrum Jülich and Dora Heras, University of Santiago de Compostela
Session Manager:
Marcel Stefko
Presentation
Discussion
Resources
Session TH4.O-4
TH4.O-4.1: PRACTICE AND EXPERIENCE IN USING PARALLEL AND SCALABLE MACHINE LEARNING IN REMOTE SENSING FROM HPC OVER CLOUD TO QUANTUM COMPUTING
Morris Riedel, University of Iceland, Iceland; Gabriele Cavallaro, Forschungszentrum Jülich, Germany; Jón Atli Benediktsson, University of Iceland, Iceland
TH4.O-4.3: Comparing area-based and feature-based methods for co-registration of multispectral bands on GPU
Álvaro Ordóñez, Dora B. Heras, Francisco Argüello, Universidade de Santiago de Compostela, Spain
TH4.O-4.4: AN FPGA-BASED IMPLEMENTATION OF A HYPERSPECTRAL ANOMALY DETECTION ALGORITHM FOR REAL-TIME APPLICATIONS
Maria Diaz, University of Las Palmas de Gran Canaria (ULPGC), Spain; Julian Caba, University of Castilla La Mancha (UCLM), Spain; Raul Guerra, University of Las Palmas de Gran Canaria (ULPGC), Spain; Jesus Barba, University of Castilla La Mancha (UCLM), Spain; Sebastian Lopez, University of Las Palmas de Gran Canaria (ULPGC), Spain
TH4.O-4.5: ENHANCING LARGE BATCH SIZE TRAINING OF DEEP MODELS FOR REMOTE SENSING APPLICATIONS
Rocco Sedona, Gabriele Cavallaro, Forschungszentrum Jülich, Germany; Morris Riedel, Matthias Book, University of Iceland, Iceland
TH4.O-4.6: EVOLUTIONARY OPTIMIZATION OF NEURAL ARCHITECTURES IN REMOTE SENSING CLASSIFICATION PROBLEMS
Daniel Coquelin, Karlsruher Institut für Technologie, Germany; Rocco Sedona, Morris Riedel, Forschungszentrum Jülich / University of Iceland, Germany; Markus Götz, Karlsruher Institut für Technologie, Germany

Quicklinks

Downloads

Programme guide