Ribana Roscher
Ribana Roscher
Research Center Jülich and University of Bonn
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
Explainable machine learning for scientific insights and discoveries
R Roscher, B Bohn, MF Duarte, J Garcke
Ieee Access 8, 42200-42216, 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
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
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
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
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
Can i trust my one-class classification?
B Mack, R Roscher, B Waske
Remote Sensing 6 (9), 8779-8802, 2014
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
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
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
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
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
Hyperspectral plant disease forecasting using generative adversarial networks
A Förster, J Behley, J Behmann, R Roscher
International Geoscience and Remote Sensing Symposium, 2019
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
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
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
I2VM: Incremental import vector machines
R Roscher, W Förstner, B Waske
Image and Vision Computing 30 (4-5), 263-278, 2012
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
Shapelet-Based Sparse Representation for Landcover Classification of Hyperspectral Images
R Roscher, B Waske
IEEE Transactions on Geoscience and Remote Sensing 54 (3), 2016
Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data
R Hagensieker, R Roscher, J Rosentreter, B Jakimow, B Waske
International journal of applied earth observation and geoinformation 63 …, 2017
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20