Publications

Q4/2021

Hassanian, R., Yeganeh, N., Unnthorsson, R. & Riedel, M. (2021). A Practical Approach for Estimating the Optimum Tilt Angle of a Photovoltaic Panel for a Long Period—Experimental Recorded Data. MDPI Journals 2021

DOI:10.3390/solar1010005

Q3/2021

Sedona, R., Cavallaro, G., Book, M. & Riedel, M. (2021). Enhancing Large Batch Size Training of Deep Models for Remote Sensing Applications. IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

DOI:10.1109/IGARSS47720.2021.9555136

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Q3/2021

Sedona, R., Paris, C., Cavallaro, G., Bruzzone, L. & Riedel, M. (2021). A High-Performance Multispectral Adaptation GAN for Harmonizing Dense Time Series of Landsat-8 and Sentinel-2 Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

DOI:10.1109/JSTARS.2021.3115604

Q3/2021

Sedona, R., Coquelin, D., Götz, M. & Riedel, M. (2021). Evolutionary Optimization of Neural Architectures in Remote Sensing Classification Problems. IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2021

DOI:10.1109/IGARSS47720.2021.9554309

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Q3/2021

Delilbasic, A., Willsch, M., Melgani, F., Cavallaro, G., Riedel, M. & Michielsen, K. (2021). Quantum Support Vector Machine Algorithms for Remote Sensing Data Classification. IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2021

DOI:10.1109/IGARSS47720.2021.9554802

ResearchGate: Download full-text PDF

Q3/2021

Benediktsson, J. A., Cavallaro, G. & Riedel, M. (2021). Practice and Experience in Using Parallel and Scalable Machine Learning in Remote Sensing from HPC Over Cloud to Quantum Computing. IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2021

DOI:10.1109/IGARSS47720.2021.9554656

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Q2/2021

Sedona, R., Barakat, C., Einarsson, P., Riedel, M., Hassanian, R., Cavallaro, G., Book, M., Neukirchen, H. & Lintermann, A. (2021). Practice and Experience in using Parallel and Scalable Machine Learning with Heterogenous Modular Supercomputing Architectures. Conference: 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

DOI:10.1109/IPDPSW52791.2021.00019

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Q4/2021

Rüttgers, M., Waldmann, M., Schröder, W. & Lintermann, A. (2021). Machine-Learning-Based Control of Perturbed and Heated Channel Flows. High Performance Computing, Proceedings of the 36th International Conference, ISC High Performance 2021

DOI:10.1007/978-3-030-90539-2_1

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