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Crop Classification

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–25 of 48 papers

TitleStatusHype
A Joint Learning Framework with Feature Reconstruction and Prediction for Incomplete Satellite Image Time Series in Agricultural Semantic SegmentationCode0
MT-CYP-Net: Multi-Task Network for Pixel-Level Crop Yield Prediction Under Very Few Samples—0
YOLO-RS: Remote Sensing Enhanced Crop Detection Methods—0
Towards more efficient agricultural practices via transformer-based crop type classification—0
SITSMamba for Crop Classification based on Satellite Image Time SeriesCode1
On the Generalizability of Foundation Models for Crop Type MappingCode0
Enhanced Infield Agriculture with Interpretable Machine Learning Approaches for Crop Classification—0
Increasing the Robustness of Model Predictions to Missing Sensors in Earth ObservationCode0
XAI-Guided Enhancement of Vegetation Indices for Crop Mapping—0
CMTNet: Convolutional Meets Transformer Network for Hyperspectral Images Classification—0
Low-Resource Crop Classification from Multi-Spectral Time Series Using Lossless CompressorsCode0
In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing DataCode0
Impact Assessment of Missing Data in Model Predictions for Earth Observation ApplicationsCode0
Enhancing crop classification accuracy by synthetic SAR-Optical data generation using deep learning—0
Cross Domain Early Crop Mapping using CropSTGAN—0
Can SAM recognize crops? Quantifying the zero-shot performance of a semantic segmentation foundation model on generating crop-type maps using satellite imagery for precision agriculture—0
PhytNet -- Tailored Convolutional Neural Networks for Custom Botanical Data—0
XAI for Early Crop Classification—0
A Comparative Assessment of Multi-view fusion learning for Crop ClassificationCode1
Boosting Crop Classification by Hierarchically Fusing Satellite, Rotational, and Contextual Data—0
Crop identification using deep learning on LUCAS crop cover photosCode0
Lightweight, Pre-trained Transformers for Remote Sensing TimeseriesCode2
The CropAndWeed Dataset: A Multi-Modal Learning Approach for Efficient Crop and Weed ManipulationCode1
Temporal Sequence Object-based CNN (TS-OCNN) for crop classification from fine resolution remote sensing image time-series—0
A Strategy Optimized Pix2pix Approach for SAR-to-Optical Image Translation Task—0
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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