High Dimensional Correspondences from Low Dimensional Manifolds - An Empirical Comparison of Graph-Based Dimensionality Reduction Algorithms. - Ribana Roscher; Falko Schindler; Wolfgang Förstner (ACCV Workshops (2), 2010)

Incremental import vector machines for large area land cover classification. - Ribana Roscher; Björn Waske; Wolfgang Förstner (ICCV Workshops, 2011)

Import vector machines based classification of multisensor remote sensing data. - Björn Waske; Ribana Roscher; Sascha Klemenjak (IGARSS, 2011)

I2VM: Incremental import vector machines. - Ribana Roscher; Wolfgang Förstner; Björn Waske (Image Vis. Comput., 2012)

Incremental Import Vector Machines for Classifying Hyperspectral Data. - Ribana Roscher; Björn Waske; Wolfgang Förstner (IEEE Trans. Geosci. Remote. Sens., 2012)

Sequential learning using incremental import vector machines for semantic segmentation. - Ribana Roscher (2012)

Superpixel-based classification of hyperspectral data using sparse representation and conditional random fields. - Ribana Roscher; Björn Waske (IGARSS, 2014)

Can I Trust My One-Class Classification? - Benjamin Mack; Ribana Roscher; Björn Waske (Remote. Sens., 2014)

Landcover classification with self-taught learning on archetypal dictionaries. - Ribana Roscher; Christoph Römer; Björn Waske; Lutz Plümer (IGARSS, 2015)

Spatio-temporal altimeter waveform retracking via sparse representation and conditional random fields. - Ribana Roscher; Bernd Uebbing; Jürgen Kusche (IGARSS, 2015)

Statistical Inference, Learning and Models in Big Data. - Beate Franke; Jean-François Plante; Ribana Roscher; Annie Lee; Cathal Smyth; Armin Hatefi; Fuqi Chen; Einat Gil; Alexander G. Schwing; Alessandro Selvitella; Michael M. Hoffman; Roger B. Grosse; et al. (CoRR, 2015)

On the benefit of topographic dictionaries for detecting disease symptoms on hyperspectral 3D plant models. - Ribana Roscher; Jan Behmann; Anne-Katrin Mahlein; Lutz Plümer (WHISPERS, 2016)

Shapelet-Based Sparse Representation for Landcover Classification of Hyperspectral Images. - Ribana Roscher; Björn Waske (IEEE Trans. Geosci. Remote. Sens., 2016)

Sparse representation-based archetypal graphs for spectral clustering. - Ribana Roscher; Lukas Drees; Susanne Wenzel (IGARSS, 2017)

Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data. - Ron Hagensieker; Ribana Roscher; Johannes Rosentreter; Benjamin Jakimow; Björn Waske (Int. J. Appl. Earth Obs. Geoinformation, 2017)

STAR: Spatio-Temporal Altimeter Waveform Retracking using Sparse Representation and Conditional Random Fields. - Ribana Roscher; Bernd Uebbing; Jürgen Kusche (CoRR, 2017)

Deep Self-taught Learning for Remote Sensing Image Classification. - Anika Bettge; Ribana Roscher; Susanne Wenzel (CoRR, 2017)

Sea Level Anomaly Prediction using Recurrent Neural Networks. - Anne Braakmann-Folgmann; Ribana Roscher; Susanne Wenzel; Bernd Uebbing; Jürgen Kusche (CoRR, 2017)

Automated Image Analysis Framework for the High-Throughput Determination of Grapevine Berry Sizes Using Conditional Random Fields. - Ribana Roscher; Katja Herzog; Annemarie Kunkel; Anna Kicherer; Reinhard Töpfer; Wolfgang Förstner (CoRR, 2017)

Subpixel Mapping of Urban Areas Using EnMAP Data and Multioutput Support Vector Regression. - Johannes Rosentreter; Ron Hagensieker; Akpona Okujeni; Ribana Roscher; Paul D. Wagner; Björn Waske (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017)

Ocean Eddy Identification and Tracking Using Neural Networks. - Katharina Franz; Ribana Roscher; Andres Milioto; Susanne Wenzel; Jürgen Kusche (IGARSS, 2018)

Archetypal Analysis for Sparse Representation-based Hyperspectral Sub-pixel Quantification. - Lukas Drees; Ribana Roscher; Susanne Wenzel (CoRR, 2018)

Inferring Routing Preferences of Bicyclists from Sparse Sets of Trajectories. - Johannes Oehrlein; Alina Förster; D. Schunck; Youness Dehbi; Ribana Roscher; Jan-Henrik Haunert (CoRR, 2018)

Foreword to the Special Issue on Machine Learning for Geospatial Data Analysis. - Jan Dirk Wegner; Ribana Roscher; Michele Volpi; Fabio Veronesi (ISPRS Int. J. Geo Inf., 2018)

Detection of Single Grapevine Berries in Images Using Fully Convolutional Neural Networks. - Laura Zabawa; Anna Kicherer; Lasse Klingbeil; Andres Milioto; Reinhard Töpfer; Heiner Kuhlmann; Ribana Roscher (CVPR Workshops, 2019)

Hyperspectral Plant Disease Forecasting Using Generative Adversarial Networks. - Alina Förster; Jens Behley; Jan Behmann; Ribana Roscher (IGARSS, 2019)

Detection of Anomalous Grapevine Berries Using All-Convolutional Autoencoders. - Laurenz Strothmann; Uwe Rascher; Ribana Roscher (IGARSS, 2019)

Automatic Differentiation of Damaged and Unharmed Grapes Using RGB Images and Convolutional Neural Networks. - Jonas Bömer; Laura Zabawa; Philipp Sieren; Anna Kicherer; Lasse Klingbeil; Uwe Rascher; Onno Muller; Heiner Kuhlmann; Ribana Roscher (ECCV Workshops (6), 2020)

A Whale's Tail - Finding the Right Whale in an Uncertain World. - Diego Marcos; Jana Kierdorf; Ted Cheeseman; Devis Tuia; Ribana Roscher (xxAI@ICML, 2020)

Explainable Machine Learning for Scientific Insights and Discoveries. - Ribana Roscher; Bastian Bohn; Marco F. Duarte; Jochen Garcke (IEEE Access, 2020)

Counting of Grapevine Berries in Images via Semantic Segmentation using Convolutional Neural Networks. - Laura Zabawa; Anna Kicherer; Lasse Klingbeil; Reinhard Töpfer; Heiner Kuhlmann; Ribana Roscher (CoRR, 2020)

ArtifiVe-Potsdam: A Benchmark for Learning with Artificial Objects for Improved Aerial Vehicle Detection. - Immanuel Weber; Jens Bongartz; Ribana Roscher (IGARSS, 2021)

Maneuver-based Trajectory Prediction for Self-driving Cars Using Spatio-temporal Convolutional Networks. - Benedikt Mersch; Thomas Höllen; Kun Zhao; Cyrill Stachniss; Ribana Roscher (IROS, 2021)

Temporal prediction and evaluation of Brassica growth in the field using conditional generative adversarial networks. - Lukas Drees; Laura Verena Junker-Frohn; Jana Kierdorf; Ribana Roscher (Comput. Electron. Agric., 2021)

Artificial and beneficial - Exploiting artificial images for aerial vehicle detection. - Immanuel Weber; Jens Bongartz; Ribana Roscher (CoRR, 2021)

Towards a Collective Agenda on AI for Earth Science Data Analysis. - Devis Tuia; Ribana Roscher; Jan Dirk Wegner; Nathan Jacobs; Xiao Xiang Zhu 001; Gustau Camps-Valls (CoRR, 2021)

Time Dependent Image Generation of Plants from Incomplete Sequences with CNN-Transformer. - Lukas Drees; Immanuel Weber; Marc Rußwurm; Ribana Roscher (GCPR, 2022)

Probabilistic Biomass Estimation with Conditional Generative Adversarial Networks. - Johannes Leonhardt; Lukas Drees; Peter Jung 001; Ribana Roscher (GCPR, 2022)

Controlled Multi-modal Image Generation for Plant Growth Modeling. - Miro Miranda; Lukas Drees; Ribana Roscher (ICPR, 2022)

Occlusion Sensitivity Analysis of Neural Network Architectures for Eddy Detection. - Eike Bolmer; Adili Abulaitijiang; Jürgen Kusche; Ribana Roscher (IGARSS, 2022)

Improving Generalization for Few-Shot Remote Sensing Classification with Meta-Learning. - Surbhi Sharma; Ribana Roscher; Morris Riedel; M. Shahbaz Memon; Gabriele Cavallaro (IGARSS, 2022)

Augmented Aerial Reality: On Fusing Synthetic and Real Airborne Imagery for Object Detection. - Immanuel Weber; Jens Bongartz; Ribana Roscher (IGARSS, 2022)

Agricultural Plant Cataloging and Establishment of a Data Framework from UAV-based Crop Images by Computer Vision. - Maurice Günder; Facundo Ramón Ispizua Yamati; Jana Kierdorf; Ribana Roscher; Anne-Katrin Mahlein; Christian Bauckhage (CoRR, 2022)

Exploring Wilderness Using Explainable Machine Learning in Satellite Imagery. - Timo T. Stomberg; Taylor Stone; Johannes Leonhardt; Ribana Roscher (CoRR, 2022)

Exploring Self-Attention for Crop-type Classification Explainability. - Ivica Obadic; Ribana Roscher; Dário Augusto Borges Oliveira; Xiao Xiang Zhu 001 (CoRR, 2022)

MapInWild: A Remote Sensing Dataset to Address the Question What Makes Nature Wild. - Burak Ekim; Timo T. Stomberg; Ribana Roscher; Michael Schmitt 003 (CoRR, 2022)

Location-aware Adaptive Denormalization: A Deep Learning Approach For Wildfire Danger Forecasting. - Mohamad Hakam Shams Eddin; Ribana Roscher; Juergen Gall (CoRR, 2022)

Behind the Leaves: Estimation of Occluded Grapevine Berries With Conditional Generative Adversarial Networks. - Jana Kierdorf; Immanuel Weber; Anna Kicherer; Laura Zabawa; Lukas Drees; Ribana Roscher (Frontiers Artif. Intell., 2022)

Explainable Machine Learning Reveals Capabilities, Redundancy, and Limitations of a Geospatial Air Quality Benchmark Dataset. - Scarlet Stadtler; Clara Betancourt; Ribana Roscher (Mach. Learn. Knowl. Extr., 2022)

Leveraging Bioclimatic Context for Supervised and Self-supervised Land Cover Classification. - Johannes Leonhardt; Lukas Drees; Jürgen Gall; Ribana Roscher (DAGM, 2023)

Inductive Conformal Prediction for Harvest-Readiness Classification of Cauliflower Plants: A Comparative Study of Uncertainty Quantification Methods. - Mohamed M. Farag; Jana Kierdorf; Ribana Roscher (ICCV (Workshops), 2023)

Analyzing the Behavior of Cauliflower Harvest-Readiness Models by Investigating Feature Relevances. - Niklas Penzel; Jana Kierdorf; Ribana Roscher; Joachim Denzler (ICCV (Workshops), 2023)

Data-Centric Digital Agriculture: A Perspective. - Ribana Roscher; Lukas Roth; Cyrill Stachniss; Achim Walter (CoRR, 2023)

Data-driven Crop Growth Simulation on Time-varying Generated Images using Multi-conditional Generative Adversarial Networks. - Lukas Drees; Dereje T. Demie; Madhuri R. Paul; Johannes Leonhardt; Sabine J. Seidel; Thomas F. Döring; Ribana Roscher (CoRR, 2023)

Data-Centric Machine Learning for Geospatial Remote Sensing Data. - Ribana Roscher; Marc Rußwurm; Caroline Gevaert; Michael Kampffmeyer; Jefersson A. dos Santos; Maria Vakalopoulou; Ronny Hänsch; Stine Hansen; Keiller Nogueira; Jonathan Prexl; Devis Tuia (CoRR, 2023)

Reliability Scores From Saliency Map Clusters for Improved Image-Based Harvest-Readiness Prediction in Cauliflower. - Jana Kierdorf; Ribana Roscher (IEEE Geosci. Remote. Sens. Lett., 2023)

Location-Aware Adaptive Normalization: A Deep Learning Approach for Wildfire Danger Forecasting. - Mohamad Hakam Shams Eddin; Ribana Roscher; Juergen Gall (IEEE Trans. Geosci. Remote. Sens., 2023)

Recognizing protected and anthropogenic patterns in landscapes using interpretable machine learning and satellite imagery. - Timo T. Stomberg; Johannes Leonhardt; Immanuel Weber; Ribana Roscher (Frontiers Artif. Intell., 2023)

GrowliFlower: An image time-series dataset for GROWth analysis of cauLIFLOWER. - Jana Kierdorf; Laura Verena Junker-Frohn; Mike Delaney; Mariele Donoso Olave; Andreas Burkart; Hannah Jaenicke; Onno Muller; Uwe Rascher; Ribana Roscher (J. Field Robotics, 2023)

Explainable Machine Learning. - Jochen Garcke; Ribana Roscher (Mach. Learn. Knowl. Extr., 2023)

A survey of uncertainty in deep neural networks. - Jakob Gawlikowski; Cedrique Rovile Njieutcheu Tassi; Mohsin Ali; Jongseok Lee; Matthias Humt; Jianxiang Feng; Anna M. Kruspe; Rudolph Triebel; Peter Jung 001; Ribana Roscher; Muhammad Shahzad 002; Wen Yang 001; et al. (Artif. Intell. Rev., 2023)

A Framework for Enhanced Decision Support in Digital Agriculture Using Explainable Machine Learning. - Ahmed Emam; Mohamed M. Farag; Jana Kierdorf; Lasse Klingbeil; Uwe Rascher; Ribana Roscher (ECCV Workshops (3), 2024)

Assessment of soil salinity using explainable machine learning methods and Landsat 8 images. - Samet Aksoy; Elif Sertel; Ribana Roscher; Aysegul Tanik; Nikou Hamzehpour (Int. J. Appl. Earth Obs. Geoinformation, 2024)

Explainability of Sub-Field Level Crop Yield Prediction using Remote Sensing. - Hiba Najjar; Miro Miranda; Marlon Nuske; Ribana Roscher; Andreas Dengel 001 (CoRR, 2024)

Estimating daily semantic segmentation maps of classified ocean eddies using sea level anomaly data from along-track altimetry. - Eike Bolmer; Adili Abulaitijiang; Jürgen Kusche; Ribana Roscher (Frontiers Artif. Intell., 2024)

Investigating the contribution of image time series observations to cauliflower harvest-readiness prediction. - Jana Kierdorf; Timo T. Stomberg; Lukas Drees; Uwe Rascher; Ribana Roscher (Frontiers Artif. Intell., 2024)

Confident Naturalness Explanation (CNE): A Framework to Explain and Assess Patterns Forming Naturalness. - Ahmed Emam; Mohamed M. Farag; Ribana Roscher (IEEE Geosci. Remote. Sens. Lett., 2024)

Leveraging Activation Maximization and Generative Adversarial Training to Recognize and Explain Patterns in Natural Areas in Satellite Imagery. - Ahmed Emam; Timo T. Stomberg; Ribana Roscher (IEEE Geosci. Remote. Sens. Lett., 2024)

Enhancing decision support in crop production: Analyzing conformal prediction for uncertainty quantification. - Mohamed M. Farag; Ahmed Emam; Johannes Leonhardt; Ribana Roscher (Comput. Electron. Agric., 2025)

Explainability of Subfield Level Crop Yield Prediction Using Remote Sensing. - Hiba Najjar; Miro Miranda; Marlon Nuske; Ribana Roscher; Andreas Dengel 001 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)

Core-Set Selection for Data-efficient Land Cover Segmentation. - Keiller Nogueira; Akram Zaytar; Wanli Ma; Ribana Roscher; Ronny Hänsch; Caleb Robinson; Anthony Ortiz; Simone Fobi Nsutezo; Rahul Dodhia; Juan M. Lavista Ferres; Oktay Karakus; Paul L. Rosin (CoRR, 2025)

Confidence-Filtered Relevance (CFR): An Interpretable and Uncertainty-Aware Machine Learning Framework for Naturalness Assessment in Satellite Imagery. - Ahmed Emam; Ribana Roscher (CoRR, 2025)