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Rocco Sedona
Rocco Sedona
Postdoctoral researcher at Forschungszentrum Jülich
Verified email at fz-juelich.de
Title
Cited by
Cited by
Year
Remote sensing big data classification with high performance distributed deep learning
R Sedona, G Cavallaro, J Jitsev, A Strube, M Riedel, JA Benediktsson
Remote Sensing 11 (24), 3056, 2019
422019
Juwels booster–a supercomputer for large-scale ai research
S Kesselheim, A Herten, K Krajsek, J Ebert, J Jitsev, M Cherti, M Langguth, ...
High Performance Computing: ISC High Performance Digital 2021 International …, 2021
212021
Practice and experience in using parallel and scalable machine learning with heterogenous modular supercomputing architectures
M Riedel, R Sedona, C Barakat, P Einarsson, R Hassanian, G Cavallaro, ...
2021 IEEE International Parallel and Distributed Processing Symposium …, 2021
162021
A high-performance multispectral adaptation GAN for harmonizing dense time series of landsat-8 and sentinel-2 images
R Sedona, C Paris, G Cavallaro, L Bruzzone, M Riedel
IEEE journal of selected topics in applied earth observations and remote …, 2021
112021
Accelerating hyperparameter tuning of a deep learning model for remote sensing image classification
M Aach, R Sedona, A Lintermann, G Cavallaro, H Neukirchen, M Riedel
IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium …, 2022
92022
End-to-End Process Orchestration of Earth Observation Data Workflows with Apache Airflow on High Performance Computing
L Tian, R Sedona, A Mozaffari, E Kreshpa, C Paris, M Riedel, MG Schultz, ...
IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium …, 2023
72023
Scaling up a Multispectral RESNET-50 to 128 GPUs
R Sedona, G Cavallaro, J Jitsev, A Strube, M Riedel, M Book
IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020
72020
Evolutionary optimization of neural architectures in remote sensing classification problems
D Coquelin, R Sedona, M Riedel, M Götz
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 1587 …, 2021
62021
Enhancing large batch size training of deep models for remote sensing applications
R Sedona, G Cavallaro, M Riedel, M Book
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 1583 …, 2021
42021
An automatic approach for the production of a time series of consistent land-cover maps based on long-short term memory
R Sedona, C Paris, L Tian, M Riedel, G Cavallaro
IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium …, 2022
32022
Exploration of machine learning methods for the classification of infrared limb spectra of polar stratospheric clouds
R Sedona, L Hoffmann, R Spang, G Cavallaro, S Griessbach, M Höpfner, ...
Atmospheric measurement techniques 13 (7), 3661-3682, 2020
32020
Sen4map: Advancing mapping with sentinel-2 by providing detailed semantic descriptions and customizable land-use and land-cover data
S Sharma, R Sedona, M Riedel, G Cavallaro, C Paris
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024
22024
Accuracy assessment of land-use-land-cover maps: the semantic gap between in situ and satellite data
C Paris, L Martinez-Sanchez, M van der Velde, S Sharma, R Sedona, ...
Image and Signal Processing for Remote Sensing XXIX 12733, 187-200, 2023
22023
Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications
D Szwarcman, S Roy, P Fraccaro, ÞE Gíslason, B Blumenstiel, R Ghosal, ...
arXiv preprint arXiv:2412.02732, 2024
12024
Scalable machine learning with high performance and cloud computing
DIG Cavallaro, MS Memon, R Sedona
IEEE international geoscience and remote sensing symposium (IGARSS)(No. FZJ …, 2020
12020
AI4HPC: Library to Train AI Models on HPC Systems using CFD Datasets
E Inanc, R Sarma, M Aach, R Sedona, A Lintermann
Workshop on Advancing Neural Network Training: Computational Efficiency …, 0
1
Downstream Applications on Prithvi: A Foundation Model for Global Geospatial Data
D Szwarcman, C Phillips, S Roy, P Fraccaro, B Blumenstiel, B Zadrozny, ...
American Geophysical Union Fall Meeting, 2024
2024
Prithvi V1. 0: Generalist Geospatial Foundation Model on Global HLS Data
D Szwarcman, S Roy, P Fraccaro, B Blumenstiel, C Phillips, B Zadrozny, ...
American Geophysical Union Fall Meeting, 2024
2024
4M4EO–Massively Multi-Modal Masked Autoencoders for Earth Observation
J Jakubik, B Blumenstiel, S Maurogiovanni, P Fraccaro, R Sedona, ...
American Geophysical Union Fall Meeting, 2024
2024
Vectorized Highly Parallel Density-based Clustering for Applications with Noise
JA Xavier, JPGH Muriedas, S Nassyr, R Sedona, M Götz, A Streit, ...
IEEE Access, 2024
2024
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