2025
Explainability of Subfield Level Crop Yield Prediction Using Remote Sensing.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025
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
Investigating the contribution of image time series observations to cauliflower harvest-readiness prediction.
Frontiers Artif. Intell., 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.
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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.
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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.
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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