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dzetsaka : AI-Powered Remote Sensing Classification QGIS 4 compatibility
QGIS 4 ready Active
Yes — dzetsaka : AI-Powered Remote Sensing Classification supports QGIS 4 (declared max version 4.99.0).
Raster classification in QGIS with 11 machine learning algorithms, Optuna hyperparameter search, SHAP explanations, class imbalance handling, and HTML reports.
About
dzetsaka is a QGIS plugin that classifies remote sensing images and other multiband rasters. - 11 classifiers: GMM, RF, SVM, KNN, XGBoost, CatBoost, ET, GBC, LR, NB, MLP - Optuna hyperparameter search - SHAP explanations and confidence maps - Class imbalance handling (SMOTE, class weights, nested CV) - Guided wizard and compact dashboard - Reusable recipes and HTML reports For documentation and updates: https://github.com/nkarasiak/dzetsaka/
| Author | Nicolas Karasiak |
|---|---|
| Downloads | 251,504 |
| Latest version | 5.1.1 |
| Last updated | 2026-10-01 (14 days ago) |
| Min QGIS | 3.0.0 |
| Max QGIS | 4.99.0 |
| QGIS 4 ready | Yes |
| Maintenance | Active |
| Categories | Remote sensing, AI & machine learning |
| Tags | classification, processing, knn, svm, random forest, machine learning, xgboost, neural network, remote sensing, class imbalance, catboost, explainability, shap, optuna, smote, earth observation, land cover, cross-validation |
Homepage · Repository · Issue tracker · Official page
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Maintenance: Active = updated within 1 year, Quiet = 1–3 years, Likely abandoned = over 3 years.