Basics of spectral imaging, Classification use-case. Active learning to improve labeling. Classification performance and fine-tuning.
Object segmentation and classification. Foreign object detection with unknown objects. Per-object performance estimation.
Regression use-case. Quantification from spectral images. Data cleaning, outlier detection and removal.
Visualization of spectral indices. Definition of custom spectral indices. Export of data and models. Model deployment using perClass Mira Runtime and perClass Batch processing.