Semantic segmentation is a computer vision task that involves classifying each pixel in an image into predefined categories, essentially providing a detailed understanding of the scene by identifying the objects and their boundaries. This approach enables algorithms to distinguish between different objects, making it fundamental for various applications like autonomous driving, medical imaging, and image editing. By assigning class labels to each pixel, semantic segmentation provides rich spatial information that can be leveraged in more complex tasks such as object detection.
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