A Benchmark Dataset, Validation Procedure and Baseline Results
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Remote Sensing 2022, MDPI, 14(21), 5526
Are Cloud Detection U-Nets Robust Against in-Orbit Image Acquisition Conditions?
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IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium
Extracting High-Resolution Cultivated Land Maps from Sentinel-2 Image Series
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IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium
Data Augmentation for Multi-Image Super-Resolution
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IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium
Semi-Simulated Training Data for Multi-Image Super-Resolution
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IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium
Building and verifying end-to-end deep learning engines to detect anomalies in spacecraft telemetry using satellite digital twins
73rd International Astronautical Congress 2022
Robustifying the deployment of the in-orbit AI for Earth observation
73rd International Astronautical Congress 2022
Toward an on-board AI proof of concept for Chime: a feasibility study
8th OBPDC 2022, 8th On-Board Payload Data Compression ESA Conference, Athens, Greece 2022
Sensitivity analysis and uncertainty quantification of thermal model for data processing unit dedicated for micro-satellite space missions
Therminic 2022, 28th International Workshop on Thermal Investigations of ICs and Systems 2022
Evaluating Hyperspectral Image Super-Resolution in Real-Life Scenarios
Whispers 2022 ESA Conference
The Hyperview Challenge: Estimating Soil Parameters from Hyperspectral Images
IEEE International Conference on Image Processing, ICIP 2022
Evaluating algorithms for anomaly detection in satellite telemetry data
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Acta Astronautica, Vol. 198, pp. 689-701, Elsevier 2022
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing
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IEEE Geoscience and Remote Sensing Letters, Vol. 19, pp. 1-5, Art no. 6011105, 2022
Graph Neural Networks Extract High-Resolution Cultivated Land Maps From Sentinel-2 Image Series
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IEEE Geoscience and Remote Sensing Letters, Vol. 19, pp. 1-5, Art no. 5513105, 2022
CHIME: The first AI-powered ESA operational mission
The Small Satellites Systems and Services Symposium 2022 (The 4S Symposium)
Understanding the Impact of Image Compression on Object Detection Using Deep Learning
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Sensors, MDPI, 2022, 22(3), 1104
Wykorzystanie wirtualnej I rozszerzonej rzeczywistości w procesie szkoleniowym
Zrównoważony Rozwój i Europejski Ład Wektorami na Drodze Doskonalenia Warsztatu Naukowca. Wydawnictwo Politechniki Śląskiej 2021
Deep Ensembles for Hyperspectral Image Data Classification and Unmixing
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emote Sensing, MDPI, 2021, 13(20), 4133
Increasing the potential of Sentinel-2 imagery with multiple-image super-resolution
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European Space Agency Earth Observation Φ-Week, Φ-Week 2021, Online Conference
Robust Cloud Detection from Satellite Images Using Deep Learning: Are We There Yet?
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European Space Agency Earth Observation Φ-Week, Φ-Week 2021, Online Conference
Quantifying the “Unquantifiable”: How to Estimate the Robustness of the On-board AI for Hyperspectral Image Analysis
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European Space Agency Earth Observation Φ-Week, Φ-Week 2021, Online Conference
Deep Learning for Multiple-Image Super-Resolution of Sentinel-2 Data
IGARSS 2021
Towards Robust Cloud Detection in Satellite Images Using U-Nets
IGARSS 2021
Investigating the Impact of the Training Set Size on Deep Learning-Powered Hyperspectral Unmixing
IGARSS 2021
Benchmarking Deep Learning for On-Board Space Applications
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Remote Sensing, MDPI, 2021
Analysis of Methods for CubeSat Mission Design Based on in-orbit Results of KRAKsat Mission
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International Journal of Education and Information Technologies, Vol. 15, 2021, pp. 295-302
Predicting risk of satellite collisions using machine learning
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Journal of Space Safety Engineering, 2021
ELSA: Euler-Lagrange Skeletal Animations - Novel and Fast Motion Model Applicable to VR/AR Devices
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Proceedings of International Conference on Computational Science 2021, Lecture Notes in Computer Science, Vol. 12746, pp. 120-133, Springer, 2021
Antelope: Towards on-board anomaly detection in telemetry data using deep learning
European Workshop on On-Board Data Processing (OBDP2021)
System-level hardening techniques used in the COTS-based data processing unit
European Workshop on On-Board Data Processing (OBDP2021)
Detecting anomalies in spacecraft telemetry using evolutionary thresholding and LSTMs
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GECCO Companion 2021: 143-144, ACM, 2021
Segmentation of hyperspectral images using self-organizing maps
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Proceedings Volume 11736, Real-Time Image Processing and Deep Learning 2021; 117360M (2021) https://doi.org/10.1117/12.2586236
Event: SPIE Defense + Commercial Sensing, 2021, Online Only
Towards On-Board Hyperspectral Satellite Image Segmentation: Understanding Robustness of Deep Learning through Simulating Acquisition Conditions
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Remote Sens. 2021, 13(8), 1532; https://doi.org/10.3390/rs13081532
Segmenting Hyperspectral Images Using Spectral Convolutional Neural Networks in the Presence of Noise
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IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. Date of Conference: 26 Sept.-2 Oct. 2020
Hyperspectral Image Classification Using Spectral-Spatial Convolutional Neural Networks
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IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. Date of Conference: 26 Sept.-2 Oct. 2020
Leopard: A new chapter in on-board deep learning-powered analysis of hyperspectral imagery
Proc. 71st International Astronautical Congress (IAC) – The CyberSpace Edition, pp. 1 – 4, 12-14 October 2020.
Toward automated collision avoidance: Predicting the risk of satellite collisions using machine learning-powered techniques
Proc. 71st International Astronautical Congress (IAC) – The CyberSpace Edition, pp. 1 – 4, 12-14 October 2020.
The size matters: On-board hyperspectral data reduction using deep learning
Proc. 7th International Workshop on On-Board Payload Data Compression, September 21-23, pp. 1 – 8, European Space Agency Conference, 2020.
Look Ma, No Ground Truth! Extracting value from multi- and hyperspectral images using unsupervised learning
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European Space Agency Earth Observation Φ-Week, Φ-Week 2020, Online Conference.
Unsupervised Feature Learning Using Recurrent Neural Nets for Segmenting Hyperspectral Images
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IEEE Geoscience and Remote Sensing Letters, pp. 1-5, 2020
Hyperspectral Band Selection Using Attention-Based Convolutional Neural Networks
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IEEE Access, vol. 8, pp 42384-42403, IEEE, 2020.
Towards resource-frugal deep convolutional neural networks for hyperspectral image segmentation
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Microprocessors and Microsystems, 102994, pp 1-44, Elsevier, 2020
Unsupervised Segmentation of Hyperspectral Images Using 3-D Convolutional Autoencoders
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IEEE Geoscience and Remote Sensing Letters, pp 1-5, 2019, DOI: 10.1109/LGRS.2019.2960945
Transfer Learning for Segmenting Dimensionally Reduced Hyperspectral Images
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IEEE Geoscience and Remote Sensing Letters, pp 1-5, 2019, DOI: 10.1109/LGRS.2019.2942832
Training- and Test-Time Data Augmentation for Hyperspectral Image Segmentation
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IEEE Geoscience and Remote Sensing Letters, pp 1-5, 2019, DOI: 10.1109/LGRS.2019.2921011
Validating hyperspectral image segmentation.
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IEEE Geoscience and Remote Sensing Letters, pp 1-5, 2019, DOI: 10.1109/LGRS.2019.2895697
On data augmentation for segmenting hyperspectral images.
Paper 10996-8, pp 1-8, Proc. SPIE Defense+Commercial Sensing 2019, Baltimore, USA, 2019 (in press)
Segmentation of multispectral data simulated from hyperspectral imagery.
pp 1-4, Proc. IEEE IGARSS 2019, Yokohama, Japan, 2019 (in press)
Segmentation of reduced hyperspectral image data, European Workshop on on-board data processing.
OBDP 2019, ESA, ESTEC, Noordwijk, The Netherlands, 2019
Accurate segmentation of hyperspectral images using deep neural networks – Are we there yet?
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PhiWeek 2018, Frascati, Italy, 2018, Video time 1:09
Selecting Features from Time Series Using Attention-Based Recurrent Neural Networks
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Lecture Notes in Computer Science book series (LNCS, volume 12644)
Multiple-Image Super-Resolution Using Deep Learning and Statistical Features
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Lecture Notes in Computer Science book series (LNCS, volume 12644)
Evaluating Super-Resolution of Satellite Images: A Proba-V Case Study
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IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. Date of Conference: 26 Sept.-2 Oct. 2020
Deep Learning for Multiple-Image Super-Resolution
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IEEE Geoscience and Remote Sensing Letters, pp 1-5, 2019, DOI: 10.1109/LGRS.2019.2940483
Super-resolution reconstruction using deep learning: should we go deeper?
Communication in Computer and Information Science, Springer 2019.
Deep Learning for Fast Super-Resolution Reconstruction from Multiple Images. Proceedings of the SPIE.
Defence+Commercial Sensing Conference 2019, Baltimore, US 2019.
B4MultiSR: A Benchmark for Multiple-Image Super-Resolution Reconstruction.
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Communications in Computer and Information Science, Springer 2018, s. 361-375.
Evaluating super-resolution reconstruction of satellite images.
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Acta Astronautica, Vol. 153, Elsevier 2018, s 15-25.
Evolving imaging model for super-resolution reconstruction.
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Proceedings of the Genetic and Evolutionary Computation Conference, Kyoto, Japan 2018, s. 284-285.
Towards Evolutionary Super-Resolution.
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Lecture Notes in Computer Science, Vol. 10784, Springer 2018, s. 480-496.
Towards Robust Evaluation of Super-Resolution Satellite Image Reconstruction.
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Lecture Notes in Computer Science, Vol. 10751, Springer 2018, s. 476-486.
Optimizing Super-resolution Reconstruction using a Genetic Algorithm.
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Proceedings of the 10th International Conference on Agents and Artificial Intelligence, Vol. 2, ScitePress 2018, s. 599-605.
Segmentation of multispectral data simulated from hyperspectral imagery
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IEEE International Geoscience and Remote Sensing Symposium - IGARSS 2019 - Yokohama, Japan - 28 July - 2 August 2019
On training deep networks for satellite image super-resolution
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IEEE International Geoscience and Remote Sensing Symposium - IGARSS 2019 - Yokohama, Japan - 28 July - 2 August 2019