Computational Intelligence for Multi-Source Remote Sensing Data Analytics

Informazioni relative al progetto

CALCHAS

ID dell’accordo di sovvenzione: 842560

DOI 10.3030/842560

Progetto chiuso

Data della firma CE 25 Aprile 2019

Data di avvio 1 Novembre 2019

Data di completamento 30 Aprile 2022

Finanziato da

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Costo totale € 215 492,16

Contributo UE € 215 492,16

Coordinato da

IDRYMA TECHNOLOGIAS KAI EREVNAS
Greece

Pubblicazioni

Peer reviewed articles (6)

Distributed Training and Inference of Deep Learning Models for Multi-Modal Land Cover Classification

Autori: Maria Aspri; Grigorios Tsagkatakis; Panagiotis Tsakalides
Pubblicato in: Remote Sensing, Numero 12(17), 2020, ISSN 2072-4292
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/rs12172670

Tensor Decomposition Learning for Compression of Multidimensional Signals

Autori: Aidini Anastasia; Tsagkatakis Grigorios; Tsakalides Panagiotis
Pubblicato in: IEEE Journal of Selected Topics in Signal Processing, Numero 1, 2021, Pagina/e 476 - 490, ISSN 1932-4553
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/JSTSP.2021.3054314

4D U-Nets for Multi-Temporal Remote Sensing Data Classification

Autori: Giannopoulos Michalis, Tsagkatakis Grigorios, Tsakalides Panagiotis
Pubblicato in: remote sensing, Numero 14(3), 2022, ISSN 2072-4292
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/rs14030634

Embedded Temporal Convolutional Networks for Essential Climate Variables Forecasting

Autori: Villia Maria Myrto; Tsagkatakis Grigorios; Moghaddam Mahta; Tsakalides Panagiotis
Pubblicato in: Sensors, Numero 2, 2022, ISSN 1424-8220
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s22051851

OmbriaNet — Supervised Flood Mapping via Convolutional Neural Networks Using Multitemporal Sentinel-1 and Sentinel-2 Data Fusion

Autori: Drakonakis Georgios; Tsagkatakis Grigorios; Fotiadou Konstantina; Tsakalides Panagiotis
Pubblicato in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Numero 15, 2022, ISSN 1939-1404
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.5281/zenodo.6674223

Quantifying the structure of strong gravitational lens potentials with uncertainty-aware deep neural networks

Autori: Georgios Vernardos, Grigorios Tsagkatakis, Yannis Pantazis
Pubblicato in: Monthly Notices of the Royal Astronomical Society, Numero 499/4, 2020, Pagina/e 5641-5652, ISSN 0035-8711
Editore: Blackwell Publishing Inc.
DOI: 10.1093/mnras/staa3201

Conference proceedings (3)

4D Convolutional Neural Networks for Multi-Spectral and Multi-Temporal Remote Sensing Data Classification

Autori: Michalis Giannopoulos; Grigorios Tsagkatakis; Panagiotis Tsakalides
Pubblicato in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022, ISBN 978-1-6654-0540-9
Editore: IEEE
DOI: 10.1109/icassp43922.2022.9746777

Deep multi-modal satellite and in-situ observation fusion for Soil Moisture retrieva

Autori: Tsagkatakis Grigorios; Moghaddam Mahta; Tsakalides Panagiotis
Pubblicato in: IEEE International Geoscience and Remote Sensing Symposium, Numero 9, 2021, ISBN 978-1-6654-0369-6
Editore: IEEE
DOI: 10.5281/zenodo.6674311

Multi-Temporal Convolutional Neural Networks for Satellite-Derived Soil Moisture Observation Enhancement

Autori: Tsagkatakis Grigorios; Moghaddam Mahta; Tsakalides Panagiotis
Pubblicato in: IEEE International Geoscience and Remote Sensing Symposium, 2020, ISBN 978-1-7281-6373-4
Editore: IEEE
DOI: 10.1109/IGARSS39084.2020.9323790