YieldSAT: A Multimodal Benchmark Dataset for High-Resolution Crop Yield Prediction
Paper • 2604.00940 • Published
Francisco Mena
panshop
AI & ML interests
AI, Remote Sensing, Multi-view Learning, Missing Data
Recent Activity
authored a paper 1 day ago
YieldSAT: A Multimodal Benchmark Dataset for High-Resolution Crop Yield Prediction commentedon a paper 3 days ago
An Analysis of Temporal Dropout in Earth Observation Time Series for
Regression Tasks commentedon a paper 3 days ago
On What Depends the Robustness of Multi-source Models to Missing Data in
Earth Observation?Organizations
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authored 12
papers 8 months ago
A Comparative Assessment of Multi-view fusion learning for Crop Classification
Paper • 2308.05407 • Published
Predicting Crop Yield With Machine Learning: An Extensive Analysis Of Input Modalities And Models On a Field and sub-field Level
Paper • 2308.08948 • Published
Adaptive Fusion of Multi-view Remote Sensing data for Optimal Sub-field Crop Yield Prediction
Paper • 2401.11844 • Published
Impact Assessment of Missing Data in Model Predictions for Earth Observation Applications
Paper • 2403.14297 • Published
Assessment of Sentinel-2 spatial and temporal coverage based on the scene classification layer
Paper • 2406.18584 • Published
XAI-Guided Enhancement of Vegetation Indices for Crop Mapping
Paper • 2407.08298 • Published
Increasing the Robustness of Model Predictions to Missing Sensors in Earth Observation
Paper • 2407.15512 • Published
In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data
Paper • 2403.16582 • Published
Missing Data as Augmentation in the Earth Observation Domain: A Multi-View Learning Approach
Paper • 2501.01132 • Published
On What Depends the Robustness of Multi-source Models to Missing Data in Earth Observation?
Paper • 2503.19719 • Published
An Analysis of Temporal Dropout in Earth Observation Time Series for Regression Tasks
Paper • 2504.06915 • Published
Common Practices and Taxonomy in Deep Multi-view Fusion for Remote Sensing Applications
Paper • 2301.01200 • Published