SOTAVerified

Crop Classification

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–48 of 48 papers

TitleStatusHype
Lightweight, Pre-trained Transformers for Remote Sensing TimeseriesCode2
SITSMamba for Crop Classification based on Satellite Image Time SeriesCode1
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
TimeMatch: Unsupervised Cross-Region Adaptation by Temporal Shift EstimationCode1
Generalized Classification of Satellite Image Time Series with Thermal Positional EncodingCode1
A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segmentation with deep learningCode1
Crop Rotation Modeling for Deep Learning-Based Parcel Classification from Satellite Time SeriesCode1
Crop Classification under Varying Cloud Cover with Neural Ordinary Differential EquationsCode1
A Comparative Assessment of Multi-view fusion learning for Crop ClassificationCode1
Impact Assessment of Missing Data in Model Predictions for Earth Observation ApplicationsCode0
End-to-End Learned Early Classification of Time Series for In-Season Crop Type MappingCode0
In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing DataCode0
Activation Regression for Continuous Domain Generalization with Applications to Crop ClassificationCode0
Low-Resource Crop Classification from Multi-Spectral Time Series Using Lossless CompressorsCode0
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
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
Crop identification using deep learning on LUCAS crop cover photosCode0
Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological SlidesCode0
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
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
Show:102550
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