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Found 6 papers, 3 papers with code
XAI for Early Crop Classification
We propose an approach for early crop classification through identifying important timesteps with eXplainable AI (XAI) methods.
Harnessing Administrative Data Inventories to Create a Reliable Transnational Reference Database for Crop Type Monitoring
With leaps in machine learning techniques and their applicationon Earth observation challenges has unlocked unprecedented performance across the domain.
Boosting Crop Classification by Hierarchically Fusing Satellite, Rotational, and Contextual Data
To evaluate our approach, we release a new annotated dataset of 7. 4 million agricultural parcels in France and Netherlands.
Privacy in Practice: Private COVID-19 Detection in X-Ray Images (Extended Version)
The introduced DP should help limit leakage threats posed by MIAs, and our practical analysis is the first to test this hypothesis on the COVID-19 classification task.
EuroCrops: A Pan-European Dataset for Time Series Crop Type Classification
We present EuroCrops, a dataset based on self-declared field annotations for training and evaluating methods for crop type classification and mapping, together with its process of acquisition and harmonisation.
[Re] Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention
Additionally, we also compiled an alternative dataset similar to the one presented in the paper and evaluated the methodology on it.
