SOTAVerified

Crop Classification

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–48 of 48 papers

TitleStatusHype
Logistic regression models for aggregated data—0
MT-CYP-Net: Multi-Task Network for Pixel-Level Crop Yield Prediction Under Very Few Samples—0
PhytNet -- Tailored Convolutional Neural Networks for Custom Botanical Data—0
Spatio-temporal Crop Classification On Volumetric Data—0
Tampered VAE for Improved Satellite Image Time Series Classification—0
Temporal Sequence Object-based CNN (TS-OCNN) for crop classification from fine resolution remote sensing image time-series—0
Time Gated Convolutional Neural Networks for Crop Classification—0
Time-Space tradeoff in deep learning models for crop classification on satellite multi-spectral image time series—0
Towards more efficient agricultural practices via transformer-based crop type classification—0
XAI for Early Crop Classification—0
XAI-Guided Enhancement of Vegetation Indices for Crop Mapping—0
Improvement in Land Cover and Crop Classification based on Temporal Features Learning from Sentinel-2 Data Using Recurrent-Convolutional Neural Network (R-CNN)—0
Impact Assessment of Missing Data in Model Predictions for Earth Observation ApplicationsCode0
Spatio-temporal crop classification of low-resolution satellite imagery with capsule layers and distributed attentionCode0
Increasing the Robustness of Model Predictions to Missing Sensors in Earth ObservationCode0
In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing DataCode0
Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological SlidesCode0
Crop identification using deep learning on LUCAS crop cover photosCode0
Low-Resource Crop Classification from Multi-Spectral Time Series Using Lossless CompressorsCode0
Activation Regression for Continuous Domain Generalization with Applications to Crop ClassificationCode0
On the Generalizability of Foundation Models for Crop Type MappingCode0
A Joint Learning Framework with Feature Reconstruction and Prediction for Incomplete Satellite Image Time Series in Agricultural Semantic SegmentationCode0
End-to-End Learned Early Classification of Time Series for In-Season Crop Type MappingCode0
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All datasetsCropHarvest - KenyaCropHarvest - TogoCropHarvest - BrazilCropHarvest - GlobalCropHarvest multicrop - Global

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PrestoR - no DWTarget Binary F10.86—Unverified
2Feature-level fusion (sum)Target Binary F10.79—Unverified
3Gated Fusion (Feature-level)Target Binary F10.77—Unverified
4Radar TS with TempCNNAverage Accuracy0.68—Unverified
5Input Fusion with TAEAverage Accuracy0.67—Unverified
#ModelMetricClaimedVerifiedStatus
1Ensemble aggregation with GRUAverage Accuracy0.84—Unverified
2Ensemble aggregationAverage Accuracy0.84—Unverified
3Decision fusion with GRUAverage Accuracy0.83—Unverified
4PrestoRTarget Binary F10.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Feature fusion with LSTMAverage Accuracy0.98—Unverified
2Hybrid fusion with LSTMAverage Accuracy0.97—Unverified
3PrestoRTarget Binary F10.89—Unverified
#ModelMetricClaimedVerifiedStatus
1Feature Gated FusionAverage Accuracy0.85—Unverified
2Input FusionAverage Accuracy0.85—Unverified
3Ensemble strategyAverage Accuracy0.83—Unverified
#ModelMetricClaimedVerifiedStatus
1Input FusionAverage Accuracy0.74—Unverified
2Feature Gated FusionAverage Accuracy0.73—Unverified
3Ensemble strategyAverage Accuracy0.72—Unverified