Semantic segmentation is a computer vision task that involves classifying each pixel in an image into predefined categories. This process allows machines to understand the content of an image at a detailed level, distinguishing between different objects and regions. For example, in an image of a street scene, the algorithm can identify pixels belonging to cars, pedestrians, and the road. The primary goal of semantic segmentation is to provide a comprehensive understanding of the scene, which is useful in various applications such as autonomous vehicles, medical imaging, and augmented reality. By accurately labeling each pixel, machines can make better decisions based on visual data.