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Crop Classification

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–48 of 48 papers

TitleStatusHype
XAI for Early Crop Classification—0
XAI-Guided Enhancement of Vegetation Indices for Crop Mapping—0
YOLO-RS: Remote Sensing Enhanced Crop Detection Methods—0
Crop and weed classification based on AutoML—0
A Strategy Optimized Pix2pix Approach for SAR-to-Optical Image Translation Task—0
Bagged Polynomial Regression and Neural Networks—0
Bayesian aggregation improves traditional single image crop classification approaches—0
Boosting Crop Classification by Hierarchically Fusing Satellite, Rotational, and Contextual Data—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
Certified robustness against physically-realizable patch attack via randomized cropping—0
CMTNet: Convolutional Meets Transformer Network for Hyperspectral Images Classification—0
Cross Domain Early Crop Mapping using CropSTGAN—0
Domain-Adversarial Training of Self-Attention Based Networks for Land Cover Classification using Multi-temporal Sentinel-2 Satellite Imagery—0
Early- and in-season crop type mapping without current-year ground truth: generating labels from historical information via a topology-based approach—0
Enhanced Infield Agriculture with Interpretable Machine Learning Approaches for Crop Classification—0
Enhancing crop classification accuracy by synthetic SAR-Optical data generation using deep learning—0
Evaluation of Three Deep Learning Models for Early Crop Classification Using Sentinel-1A Imagery Time Series—A Case Study in Zhanjiang, China—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
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
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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