Utilizes machine learning algorithms to classify regions based on a trained Intellesis (Link) model (based on random forest pixel classification) or an imported deep learning network, e.g., ONNX models or models trained on arivis Cloud.

Use case: Labeling image regions defined by classes in a previously trained model.

For information on labeling/annotating images to train a model on arivis Cloud, see Annotation of Images for Model Training on arivis Cloud.

For general information about arivis Cloud, see arivis Cloud Overview.

Post-processing tools in the 2D Toolkit in ZEN and ZEN core allow further refinement of semantic segmentation results, such as fill holes / binary operations and separation algorithms such as watershed.