| Training-and test-time data augmentation for hyperspectral image segmentation J Nalepa, M Myller, M Kawulok IEEE Geoscience and Remote Sensing Letters 17 (2), 292-296, 2019 | 100 | 2019 |
| Validating hyperspectral image segmentation J Nalepa, M Myller, M Kawulok IEEE Geoscience and Remote Sensing Letters 16 (8), 1264-1268, 2019 | 86 | 2019 |
| Unsupervised segmentation of hyperspectral images using 3-D convolutional autoencoders J Nalepa, M Myller, Y Imai, K Honda, T Takeda, M Antoniak IEEE Geoscience and Remote Sensing Letters 17 (11), 1948-1952, 2020 | 70 | 2020 |
| Towards resource-frugal deep convolutional neural networks for hyperspectral image segmentation J Nalepa, M Antoniak, M Myller, PR Lorenzo, M Marcinkiewicz Microprocessors and Microsystems 73, 102994, 2020 | 48 | 2020 |
| Towards on-board hyperspectral satellite image segmentation: Understanding robustness of deep learning through simulating acquisition conditions J Nalepa, M Myller, M Cwiek, L Zak, T Lakota, L Tulczyjew, M Kawulok Remote sensing 13 (8), 1532, 2021 | 38 | 2021 |
| Transfer learning for segmenting dimensionally reduced hyperspectral images J Nalepa, M Myller, M Kawulok IEEE Geoscience and Remote Sensing Letters 17 (7), 1228-1232, 2019 | 26 | 2019 |
| Hyperspectral data augmentation J Nalepa, M Myller, M Kawulok arXiv preprint arXiv:1903.05580, 2019 | 23 | 2019 |
| Benchmarking deep learning for on-board space applications M Ziaja, P Bosowski, M Myller, G Gajoch, M Gumiela, J Protich, K Borda, ... Remote Sensing 13 (19), 3981, 2021 | 21 | 2021 |
| Evaluating algorithms for anomaly detection in satellite telemetry data J Nalepa, M Myller, J Andrzejewski, P Benecki, S Piechaczek, ... Acta Astronautica 198, 689-701, 2022 | 18 | 2022 |
| The hyperview challenge: Estimating soil parameters from hyperspectral images J Nalepa, B Le Saux, N Longépé, L Tulczyjew, M Myller, M Kawulok, ... 2022 IEEE International Conference on Image Processing (ICIP), 4268-4272, 2022 | 11 | 2022 |
| Deep ensembles for hyperspectral image data classification and unmixing J Nalepa, M Myller, L Tulczyjew, M Kawulok Remote Sensing 13 (20), 4133, 2021 | 11 | 2021 |
| On data augmentation for segmenting hyperspectral images J Nalepa, M Myller, M Kawulok, B Smolka Real-Time Image Processing and Deep Learning 2019 10996, 27-34, 2019 | 4 | 2019 |
| Genetic selection of training sets for (not only) artificial neural networks J Nalepa, M Myller, S Piechaczek, K Hrynczenko, M Kawulok Beyond Databases, Architectures and Structures. Facing the Challenges of …, 2018 | 4 | 2018 |
| Predicting risk of satellite collisions using machine learning L Tulczyjew, M Myller, M Kawulok, D Kostrzewa, J Nalepa Journal of Space Safety Engineering 8 (4), 339-344, 2021 | 3 | 2021 |
| Hyperspectral image classification using spectral-spatial convolutional neural networks J Nalepa, L Tulczyjew, M Myller, M Kawulok IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 3 | 2020 |
| Segmenting hyperspectral images using spectral-spatial convolutional neural networks with training-time data augmentation J Nalepa, L Tulczyjew, M Myller, M Kawulok arXiv preprint arXiv:1907.11935, 2019 | 3 | 2019 |
| Multi-scale voting classifiers for breast-cancer histology images J Nalepa, S Piechaczek, M Myller, K Hrynczenko Advances in Intelligent Networking and Collaborative Systems: The 10th …, 2019 | 3 | 2019 |
| Selecting features from time series using attention-based recurrent neural networks M Myller, M Kawulok, J Nalepa Joint IAPR International Workshops on Statistical Techniques in Pattern …, 2021 | 2 | 2021 |
| Particle swarm optimization configures the route minimization algorithm T Jastrzab, M Myller, L Tulczyjew, M Blocho, W Ryczko, M Kawulok, ... International Conference on Computational Science, 80-87, 2022 | 1 | 2022 |
| Standardized validation of vehicle routing algorithms T Jastrzab, M Myller, L Tulczyjew, M Blocho, M Kawulok, A Czornik, ... Applied Intelligence, 1-30, 2024 | | 2024 |
