Semantic Segmentation

In the context of AI driven image segmentation, semantic segmentation refers to the process of labeling specific objects or regions in an image with their corresponding class labels.

This technique goes beyond traditional image segmentation by not only distinguishing the different foreground objects in an image but also assigning meaningful semantic labels to each pixel of those objects. It involves understanding and analyzing an image at a pixel level to identify and label the various objects present.

By using advanced deep learning algorithms and computer vision techniques, semantic segmentation helps in a wide range of applications such as autonomous driving, medical imaging, and video surveillance.

With semantic segmentation, AI models can accurately differentiate between object classes, leading to more precise object detection, scene understanding, and image analysis. It enables machines to understand images with human-like perception and enables them to make informed decisions based on the identified objects or regions.