Crop Classification
15 papers with code • 5 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Crop Classification
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CropAndWeed Dataset
EuroCrops
Sen4AgriNet
Most implemented papers
Activation Regression for Continuous Domain Generalization with Applications to Crop Classification
Geographic variance in satellite imagery impacts the ability of machine learning models to generalise to new regions.
Lightweight, Pre-trained Transformers for Remote Sensing Timeseries
Machine learning methods for satellite data have a range of societally relevant applications, but labels used to train models can be difficult or impossible to acquire.
Crop identification using deep learning on LUCAS crop cover photos
The aim of this paper is to select and publish a subset of LUCAS Cover photos for 12 mature major crops across the EU, to deploy, benchmark, and identify the best configuration of Mobile-net for the classification task, to showcase the possibility of using entropy-based metrics for post-processing of results, and finally to show the applications and limitations of the model in a practical and policy relevant context.
A Comparative Assessment of Multi-view fusion learning for Crop Classification
fmenat/multiviewcropclassification
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Instead, we present a comparison of multi-view fusion methods for three different datasets and show that, depending on the test region, different methods obtain the best performance.
Impact Assessment of Missing Data in Model Predictions for Earth Observation Applications
fmenat/missingviews-study-eo
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In this work, we assess the impact of missing temporal and static EO sources in trained models across four datasets with classification and regression tasks.
