Crop Yield Prediction: an Operational Approach to Crop Yield Modeling on Field and Sub-Field Level with Machine Learning Models

@inproceedings{pub13485,
    author = {

Helber, Patrick
 and 

Bischke, Benjamin
 and 

Habelitz, Peter
 and 

Sanchez, Cristhian
 and 

Pathak, Deepak Kumar
 and 

Miranda Lorenz, Miro
 and 

Najjar, Hiba
 and 

Mena, Francisco
 and 

Siddamsetty, Jayanth
 and 

Arenas, Diego
 and 

Vollmer, Michaela
 and 

Charfuelan Oliva, Marcela
 and 

Nuske, Marlon
 and 

Dengel, Andreas
},
    title = {Crop Yield Prediction: an Operational Approach to Crop Yield Modeling on Field and Sub-Field Level with Machine Learning Models},
    booktitle = {2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE International Geoscience and Remote Sensing Symposium (IGARSS-2023), July 16-21, Pasadena, CA, United States},
    year = {2023},
    month = {10},
    publisher = {IEEE}
}