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Crop Classification

Papers

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Showing 1–25 of 48 papers

TitleStatusHype
Lightweight, Pre-trained Transformers for Remote Sensing TimeseriesCode2
A Comparative Assessment of Multi-view fusion learning for Crop ClassificationCode1
A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segmentation with deep learningCode1
TimeMatch: Unsupervised Cross-Region Adaptation by Temporal Shift EstimationCode1
SITSMamba for Crop Classification based on Satellite Image Time SeriesCode1
Crop Classification under Varying Cloud Cover with Neural Ordinary Differential EquationsCode1
The CropAndWeed Dataset: A Multi-Modal Learning Approach for Efficient Crop and Weed ManipulationCode1
Crop mapping from image time series: deep learning with multi-scale label hierarchiesCode1
Crop Rotation Modeling for Deep Learning-Based Parcel Classification from Satellite Time SeriesCode1
Generalized Classification of Satellite Image Time Series with Thermal Positional EncodingCode1
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
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
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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