Ribana Roscher

Orcid: 0000-0003-0094-6210

According to our database1, Ribana Roscher authored at least 66 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Leveraging Activation Maximization and Generative Adversarial Training to Recognize and Explain Patterns in Natural Areas in Satellite Imagery.
IEEE Geosci. Remote. Sens. Lett., 2024

Confident Naturalness Explanation (CNE): A Framework to Explain and Assess Patterns Forming Naturalness.
IEEE Geosci. Remote. Sens. Lett., 2024

Estimating daily semantic segmentation maps of classified ocean eddies using sea level anomaly data from along-track altimetry.
Frontiers Artif. Intell., 2024

Explainability of Sub-Field Level Crop Yield Prediction using Remote Sensing.
CoRR, 2024

Assessment of soil salinity using explainable machine learning methods and Landsat 8 images.
Int. J. Appl. Earth Obs. Geoinformation, 2024

2023
A survey of uncertainty in deep neural networks.
Artif. Intell. Rev., October, 2023

Explainable Machine Learning.
Mach. Learn. Knowl. Extr., March, 2023

GrowliFlower: An image time-series dataset for GROWth analysis of cauLIFLOWER.
J. Field Robotics, March, 2023

Recognizing protected and anthropogenic patterns in landscapes using interpretable machine learning and satellite imagery.
Frontiers Artif. Intell., February, 2023

Location-Aware Adaptive Normalization: A Deep Learning Approach for Wildfire Danger Forecasting.
IEEE Trans. Geosci. Remote. Sens., 2023

Reliability Scores From Saliency Map Clusters for Improved Image-Based Harvest-Readiness Prediction in Cauliflower.
IEEE Geosci. Remote. Sens. Lett., 2023

Data-Centric Machine Learning for Geospatial Remote Sensing Data.
CoRR, 2023

Data-driven Crop Growth Simulation on Time-varying Generated Images using Multi-conditional Generative Adversarial Networks.
CoRR, 2023

Data-Centric Digital Agriculture: A Perspective.
CoRR, 2023

Analyzing the Behavior of Cauliflower Harvest-Readiness Models by Investigating Feature Relevances.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Inductive Conformal Prediction for Harvest-Readiness Classification of Cauliflower Plants: A Comparative Study of Uncertainty Quantification Methods.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Leveraging Bioclimatic Context for Supervised and Self-supervised Land Cover Classification.
Proceedings of the Pattern Recognition - 45th DAGM German Conference, 2023

2022
Explainable Machine Learning Reveals Capabilities, Redundancy, and Limitations of a Geospatial Air Quality Benchmark Dataset.
Mach. Learn. Knowl. Extr., 2022

Behind the Leaves: Estimation of Occluded Grapevine Berries With Conditional Generative Adversarial Networks.
Frontiers Artif. Intell., 2022

Location-aware Adaptive Denormalization: A Deep Learning Approach For Wildfire Danger Forecasting.
CoRR, 2022

MapInWild: A Remote Sensing Dataset to Address the Question What Makes Nature Wild.
CoRR, 2022

Exploring Self-Attention for Crop-type Classification Explainability.
CoRR, 2022

Exploring Wilderness Using Explainable Machine Learning in Satellite Imagery.
CoRR, 2022

Agricultural Plant Cataloging and Establishment of a Data Framework from UAV-based Crop Images by Computer Vision.
CoRR, 2022

Augmented Aerial Reality: On Fusing Synthetic and Real Airborne Imagery for Object Detection.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

Improving Generalization for Few-Shot Remote Sensing Classification with Meta-Learning.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

Occlusion Sensitivity Analysis of Neural Network Architectures for Eddy Detection.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

Controlled Multi-modal Image Generation for Plant Growth Modeling.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

Probabilistic Biomass Estimation with Conditional Generative Adversarial Networks.
Proceedings of the Pattern Recognition, 2022

Time Dependent Image Generation of Plants from Incomplete Sequences with CNN-Transformer.
Proceedings of the Pattern Recognition, 2022

2021
Towards a Collective Agenda on AI for Earth Science Data Analysis.
CoRR, 2021

Artificial and beneficial - Exploiting artificial images for aerial vehicle detection.
CoRR, 2021

Temporal prediction and evaluation of Brassica growth in the field using conditional generative adversarial networks.
Comput. Electron. Agric., 2021

Maneuver-based Trajectory Prediction for Self-driving Cars Using Spatio-temporal Convolutional Networks.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

ArtifiVe-Potsdam: A Benchmark for Learning with Artificial Objects for Improved Aerial Vehicle Detection.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020
Counting of Grapevine Berries in Images via Semantic Segmentation using Convolutional Neural Networks.
CoRR, 2020

Explainable Machine Learning for Scientific Insights and Discoveries.
IEEE Access, 2020

A Whale's Tail - Finding the Right Whale in an Uncertain World.
Proceedings of the xxAI - Beyond Explainable AI, 2020

Automatic Differentiation of Damaged and Unharmed Grapes Using RGB Images and Convolutional Neural Networks.
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

2019
Detection of Anomalous Grapevine Berries Using All-Convolutional Autoencoders.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Hyperspectral Plant Disease Forecasting Using Generative Adversarial Networks.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Detection of Single Grapevine Berries in Images Using Fully Convolutional Neural Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018
Foreword to the Special Issue on Machine Learning for Geospatial Data Analysis.
ISPRS Int. J. Geo Inf., 2018

Inferring Routing Preferences of Bicyclists from Sparse Sets of Trajectories.
CoRR, 2018

Archetypal Analysis for Sparse Representation-based Hyperspectral Sub-pixel Quantification.
CoRR, 2018

Ocean Eddy Identification and Tracking Using Neural Networks.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Subpixel Mapping of Urban Areas Using EnMAP Data and Multioutput Support Vector Regression.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017

Automated Image Analysis Framework for the High-Throughput Determination of Grapevine Berry Sizes Using Conditional Random Fields.
CoRR, 2017

Sea Level Anomaly Prediction using Recurrent Neural Networks.
CoRR, 2017

Deep Self-taught Learning for Remote Sensing Image Classification.
CoRR, 2017

STAR: Spatio-Temporal Altimeter Waveform Retracking using Sparse Representation and Conditional Random Fields.
CoRR, 2017

Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data.
Int. J. Appl. Earth Obs. Geoinformation, 2017

Sparse representation-based archetypal graphs for spectral clustering.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

2016
Shapelet-Based Sparse Representation for Landcover Classification of Hyperspectral Images.
IEEE Trans. Geosci. Remote. Sens., 2016

On the benefit of topographic dictionaries for detecting disease symptoms on hyperspectral 3D plant models.
Proceedings of the 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2016

2015
Statistical Inference, Learning and Models in Big Data.
CoRR, 2015

Spatio-temporal altimeter waveform retracking via sparse representation and conditional random fields.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

Landcover classification with self-taught learning on archetypal dictionaries.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

2014
Can I Trust My One-Class Classification?
Remote. Sens., 2014

Superpixel-based classification of hyperspectral data using sparse representation and conditional random fields.
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014

2012
Sequential learning using incremental import vector machines for semantic segmentation.
PhD thesis, 2012

Incremental Import Vector Machines for Classifying Hyperspectral Data.
IEEE Trans. Geosci. Remote. Sens., 2012

I<sup>2</sup>VM: Incremental import vector machines.
Image Vis. Comput., 2012

2011
Import vector machines based classification of multisensor remote sensing data.
Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium, 2011

Incremental import vector machines for large area land cover classification.
Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011

2010
High Dimensional Correspondences from Low Dimensional Manifolds - An Empirical Comparison of Graph-Based Dimensionality Reduction Algorithms.
Proceedings of the Computer Vision - ACCV 2010 Workshops, 2010


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