78 citations · 144 across the 11 of their papers we have counts for
5 papers · 1 filter
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…
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…
Predicting Crop Yield With Machine Learning: An Extensive Analysis Of Input Modalities And Models On a Field and sub-field Level
Deepak Pathak, Miro Miranda, Francisco Mena +11
We introduce a simple yet effective early fusion method for crop yield prediction that handles multiple input modalities with different temporal and spatial resolutions. We use hig…
A Comparative Assessment of Multi-view fusion learning for Crop Classification
Francisco Mena, Diego Arenas, Marlon Nuske +1
With a rapidly increasing amount and diversity of remote sensing (RS) data sources, there is a strong need for multi-view learning modeling. This is a complex task when considering…
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…