78 citations · 197 across the 22 of their papers we have counts for
10 papers · 1 filter
Exploring Physics-Informed Neural Networks for Crop Yield Loss Forecasting
Miro Miranda, Marcela Charfuelan, Andreas Dengel
In response to climate change, assessing crop productivity under extreme weather conditions is essential to enhance food security. Crop simulation models, which align with physical…
Data-Centric Machine Learning for Earth Observation: Necessary and Sufficient Features
Hiba Najjar, Marlon Nuske, Andreas Dengel
The availability of temporal geospatial data in multiple modalities has been extensively leveraged to enhance the performance of machine learning models. While efforts on the desig…
Quantum Annealing-Based Algorithm for Efficient Coalition Formation Among LEO Satellites
Supreeth Mysore Venkatesh, Antonio Macaluso, Marlon Nuske +2
The increasing number of Low Earth Orbit (LEO) satellites, driven by lower manufacturing and launch costs, is proving invaluable for Earth observation missions and low-latency inte…
XAI-Guided Enhancement of Vegetation Indices for Crop Mapping
Hiba Najjar, Francisco Mena, Marlon Nuske +1
Vegetation indices allow to efficiently monitor vegetation growth and agricultural activities. Previous generations of satellites were capturing a limited number of spectral bands,…
Explainability of Sub-Field Level Crop Yield Prediction using Remote Sensing
Hiba Najjar, Miro Miranda, Marlon Nuske +2
Crop yield forecasting plays a significant role in addressing growing concerns about food security and guiding decision-making for policymakers and farmers. When deep learning is e…
Increasing the Robustness of Model Predictions to Missing Sensors in Earth Observation
Francisco Mena, Diego Arenas, Andreas Dengel
Multi-sensor ML models for EO aim to enhance prediction accuracy by integrating data from various sources. However, the presence of missing data poses a significant challenge, part…
Assessment of Sentinel-2 spatial and temporal coverage based on the scene classification layer
Cristhian Sanchez, Francisco Mena, Marcela Charfuelan +2
Since the launch of the Sentinel-2 (S2) satellites, many ML models have used the data for diverse applications. The scene classification layer (SCL) inside the S2 product provides…
Qubit-efficient Variational Quantum Algorithms for Image Segmentation
Supreeth Mysore Venkatesh, Antonio Macaluso, Marlon Nuske +2
Quantum computing is expected to transform a range of computational tasks beyond the reach of classical algorithms. In this work, we examine the application of variational quantum…
In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data
Francisco Mena, Diego Arenas, Andreas Dengel
Studying and analyzing cropland is a difficult task due to its dynamic and heterogeneous growth behavior. Usually, diverse data sources can be collected for its estimation. Althoug…
Adaptive Fusion of Multi-view Remote Sensing data for Optimal Sub-field Crop Yield Prediction
Francisco Mena, Deepak Pathak, Hiba Najjar +11
Accurate crop yield prediction is of utmost importance for informed decision-making in agriculture, aiding farmers, and industry stakeholders. However, this task is complex and dep…