Segmentation is essential for image analysis tasks. Semantic segmentation describes the process of associating each pixel of an image with a class label, (such as flower, person, road, sky, ocean, or car).
Applications for semantic segmentation include:
Classification of terrain visible in satellite imagery
Medical imaging analysis
The steps for training a semantic segmentation network are as follows:
You can use the Image Labeler app to interactively label pixels and export the label data for training. The app can also be used to label rectangular regions of interest (ROIs) and scene labels for image classification.