| Explainable machine learning for scientific insights and discoveries R Roscher, B Bohn, MF Duarte, J Garcke Ieee Access 8, 42200-42216, 2020 | 849 | 2020 |
| A survey of uncertainty in deep neural networks J Gawlikowski, CRN Tassi, M Ali, J Lee, M Humt, J Feng, A Kruspe, ... Artificial Intelligence Review 56 (Suppl 1), 1513-1589, 2023 | 847 | 2023 |
| Automated image analysis framework for high-throughput determination of grapevine berry sizes using conditional random fields R Roscher, K Herzog, A Kunkel, A Kicherer, R Töpfer, W Förstner Computers and Electronics in Agriculture 100, 148-158, 2014 | 114 | 2014 |
| Counting of grapevine berries in images via semantic segmentation using convolutional neural networks L Zabawa, A Kicherer, L Klingbeil, R Töpfer, H Kuhlmann, R Roscher ISPRS Journal of Photogrammetry and Remote Sensing 164, 73-83, 2020 | 106 | 2020 |
| Ocean Eddy Identification and Tracking using Neural Networks K Franz, R Roscher, A Milioto, S Wenzel, J Kusche International Geoscience and Remote Sensing Symposium, 2018 | 86 | 2018 |
| Statistical Inference, Learning and Models in Big Data B Franke, JF Plante, R Roscher, A Lee, C Smyth, A Hatefi, F Chen, E Gil, ... International Statistical Review, 2016 | 83 | 2016 |
| Can i trust my one-class classification? B Mack, R Roscher, B Waske Remote Sensing 6 (9), 8779-8802, 2014 | 58 | 2014 |
| Toward a collective agenda on ai for earth science data analysis D Tuia, R Roscher, JD Wegner, N Jacobs, X Zhu, G Camps-Valls IEEE Geoscience and Remote Sensing Magazine 9 (2), 88-104, 2021 | 57 | 2021 |
| Detection of Single Grapevine Berries in Images Using Fully Convolutional Neural Networks L Zabawa, A Kicherer, L Klingbeil, A Milioto, R Töpfer, H Kuhlmann, ... CVPR Workshop on Computer Vision Problems in Plant Phenotyping, 2019 | 54 | 2019 |
| Detection of Disease Symptoms on Hyperspectral 3D Plant Models R Roscher, J Behmann, AK Mahlein, J Dupuis, H Kuhlmann, L Plümer ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information …, 2016 | 49 | 2016 |
| Mapping raised bogs with an iterative one-class classification approach B Mack, R Roscher, S Stenzel, H Feilhauer, S Schmidtlein, B Waske ISPRS Journal of Photogrammetry and Remote Sensing 120, 53-64, 2016 | 48 | 2016 |
| BAT (Berry Analysis Tool): A high-throughput image interpretation tool to acquire the number, diameter, and volume of grapevine berries A Kicherer, R Roscher, K Herzog, S Šimon, W Förstner, R Töpfer VITIS-Journal of Grapevine Research 52 (3), 129, 2013 | 46 | 2013 |
| Incremental import vector machines for classifying hyperspectral data R Roscher, B Waske, W Forstner IEEE Transactions on Geoscience and Remote Sensing 50 (9), 3463-3473, 2012 | 45 | 2012 |
| Hyperspectral plant disease forecasting using generative adversarial networks A Förster, J Behley, J Behmann, R Roscher International Geoscience and Remote Sensing Symposium, 2019 | 44 | 2019 |
| Sea Level Anomaly Prediction using Recurrent Neural Networks A Braakmann-Folgmann, R Roscher, S Wenzel, B Uebbing, J Kusche Proceedings of the 2017 conference on Big Data from Space, 2017 | 41 | 2017 |
| STAR: Spatio-temporal altimeter waveform retracking using sparse representation and conditional random fields R Roscher, B Uebbing, J Kusche Remote Sensing of Environment 201, 148-164, 2017 | 39 | 2017 |
| Initial steps for high-throughput phenotyping in vineyards K Herzog, R Roscher, M Wieland, A Kicherer, T Läbe, W Förstner, ... VITIS-Journal of Grapevine Research 53 (1), 1, 2014 | 39 | 2014 |
| I2VM: Incremental import vector machines R Roscher, W Förstner, B Waske Image and Vision Computing 30 (4-5), 263-278, 2012 | 39 | 2012 |
| Maneuver-based trajectory prediction for self-driving cars using spatio-temporal convolutional networks B Mersch, T Höllen, K Zhao, C Stachniss, R Roscher 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 36 | 2021 |
| SEMCITY TOULOUSE: A BENCHMARK FOR BUILDING INSTANCE SEGMENTATION IN SATELLITE IMAGES R Roscher, M Volpi, C Mallet, L Drees, JD Wegner ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2020 | 36 | 2020 |
Björn WaskeUniversity Osnabrück在 uos.de 的电子邮件经过验证
