Semantic Segmentation

Semantic segmentation is a computer vision task that involves classifying each pixel in an image into predefined categories. This technique enables the model to understand the content of the image at a granular level, distinguishing between different objects and backgrounds. Main characteristics include its ability to produce detailed segmentation maps, where every pixel is assigned a class label. Common use cases for semantic segmentation include autonomous driving, where it helps in identifying road signs and pedestrians, and medical imaging, where it assists in locating tumors or other anomalies in scans. By providing precise localization of objects, semantic segmentation enhances the understanding of visual data.