78 citations · 181 across the 10 of their papers we have counts for
11 papers
YieldSAT: A Multimodal Benchmark Dataset for High-Resolution Crop Yield Prediction
Miro Miranda, Deepak Pathak, Patrick Helber +10
Crop yield prediction requires substantial data to train scalable models. However, creating yield prediction datasets is constrained by high acquisition costs, heterogeneous data q…
Intrinsic Explainability of Multimodal Learning for Crop Yield Prediction
Hiba Najjar, Deepak Pathak, Marlon Nuske +1
Multimodal learning enables various machine learning tasks to benefit from diverse data sources, effectively mimicking the interplay of different factors in real-world applications…
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…
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…
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…
Q-Seg: Quantum Annealing-Based Unsupervised Image Segmentation
Supreeth Mysore Venkatesh, Antonio Macaluso, Marlon Nuske +2
We present Q-Seg, a novel unsupervised image segmentation method based on quantum annealing, tailored for existing quantum hardware. We formulate the pixel-wise segmentation proble…
Common Practices and Taxonomy in Deep Multi-view Fusion for Remote Sensing Applications
Francisco Mena, Diego Arenas, Marlon Nuske +1
The advances in remote sensing technologies have boosted applications for Earth observation. These technologies provide multiple observations or views with different levels of info…