| On understanding big data impacts in remotely sensed image classification using support vector machine methods G Cavallaro, M Riedel, M Richerzhagen, JA Benediktsson, A Plaza IEEE journal of selected topics in applied earth observations and remote …, 2015 | 130 | 2015 |
| Automatic framework for spectral–spatial classification based on supervised feature extraction and morphological attribute profiles P Ghamisi, JA Benediktsson, G Cavallaro, A Plaza IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2014 | 122 | 2014 |
| Approaching remote sensing image classification with ensembles of support vector machines on the d-wave quantum annealer G Cavallaro, D Willsch, M Willsch, K Michielsen, M Riedel IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 48 | 2020 |
| Automatic attribute profiles G Cavallaro, N Falco, M Dalla Mura, JA Benediktsson IEEE Transactions on Image Processing 26 (4), 1859-1872, 2017 | 48 | 2017 |
| Quantum support vector machine algorithms for remote sensing data classification A Delilbasic, G Cavallaro, M Willsch, F Melgani, M Riedel, K Michielsen 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2608 …, 2021 | 43 | 2021 |
| Extended Self-Dual Attribute Profiles for the Classification of Hyperspectral Images G Cavallaro, M Dalla Mura, JA Benediktsson, L Bruzzone IEEE, 2015 | 43 | 2015 |
| 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 | 40 | 2019 |
| Remote sensing image classification using attribute filters defined over the tree of shapes G Cavallaro, M Dalla Mura, JA Benediktsson, A Plaza IEEE Transactions on Geoscience and Remote Sensing 54 (7), 3899-3911, 2016 | 39 | 2016 |
| Cloud deep networks for hyperspectral image analysis JM Haut, JA Gallardo, ME Paoletti, G Cavallaro, J Plaza, A Plaza, ... IEEE transactions on geoscience and remote sensing 57 (12), 9832-9848, 2019 | 32 | 2019 |
| The influence of sampling methods on pixel-wise hyperspectral image classification with 3D convolutional neural networks J Lange, G Cavallaro, M Götz, E Erlingsson, M Riedel IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018 | 28 | 2018 |
| Parallel computation of component trees on distributed memory machines M Götz, G Cavallaro, T Géraud, M Book, M Riedel IEEE transactions on parallel and distributed systems 29 (11), 2582-2598, 2018 | 27 | 2018 |
| Smart data analytics methods for remote sensing applications G Cavallaro, M Riedel, JA Benediktsson, M Goetz, T Runarsson, ... 2014 IEEE geoscience and remote sensing symposium, 1405-1408, 2014 | 22 | 2014 |
| On scalable data mining techniques for earth science M Götz, M Richerzhagen, C Bodenstein, G Cavallaro, P Glock, M Riedel, ... Procedia computer science 51, 2188-2197, 2015 | 21 | 2015 |
| A single-step multiclass SVM based on quantum annealing for remote sensing data classification A Delilbasic, B Le Saux, M Riedel, K Michielsen, G Cavallaro IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 | 18 | 2023 |
| 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 | 18 | 2021 |
| Practice and experience in using parallel and scalable machine learning in remote sensing from HPC over cloud to quantum computing M Riedel, G Cavallaro, JA Benediktsson 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 1571 …, 2021 | 17 | 2021 |
| Deep-Learning-Based 3-D Surface Reconstruction—A Survey A Farshian, M Götz, G Cavallaro, C Debus, M Nießner, JA Benediktsson, ... Proceedings of the IEEE, 2023 | 16 | 2023 |
| Quantum svr for chlorophyll concentration estimation in water with remote sensing E Pasetto, M Riedel, F Melgani, K Michielsen, G Cavallaro IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2022 | 16 | 2022 |
| 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 | 16 | 2021 |
| High-Performance and Disruptive Computing in Remote Sensing: HDCRS—A new Working Group of the GRSS Earth Science Informatics Technical Committee [Technical Committees] G Cavallaro, DB Heras, Z Wu, M Maskey, S Lopez, P Gawron, M Coca, ... IEEE geoscience and remote sensing magazine 10 (2), 329-345, 2022 | 15 | 2022 |
Prof. Dr.-Ing. Morris RiedelProfessor of High Performance Computing & Machine Learning, Forschungszentrum Juelich & UoIcelandBestätigte E-Mail-Adresse bei fz-juelich.de
