fmenat / optimal-multiview-crop-classifier

Public repository of our work in the search for an optimal multi-view crop classifier (considering encoder architectures and fusion strategies)

In the search for an optimal multi-view crop classifier

Public repository of our work in the search for an optimal multi-view crop classifier

Data

The data used comes from https://github.com/nasaharvest/cropharvest. However we also share the code used to generate the data structures that we used in data folder.

Training

• To train the Input fusion strategy:

python train_singleview.py -s config/singleview_ex.yaml

• To train the Ensemble aggregation strategy:

python train_singleview_pool.py -s config/singleviewpool_ex.yaml

• To train strategies based on multiple encoders: Feature, Decision and Hybrid fusion strategies:

python train_multiview.py -s config/multiview_ex.yaml

Evaluation

• To evaluate the model by its predictions (performance):

python evaluate_predictions.py -s config/evaluation_ex.yaml

Installation

Please install the required packages with the following command:

pip install -r requirements.txt

📜 Source

Mena, Francisco, Diego Arenas, and Andreas Dengel. "In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data.", 2024.

• 🔓 Preprint