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Semantic Segmentation involves labeling each pixel of an image with a specific class, enabling a more nuanced understanding of visual data than traditional image classification techniques. In the context of Computer Vision, it represents a critical step towards achieving robust scene understanding, which is essential for applications such as autonomous vehicles and augmented reality. By discerning the precise location and extent of objects within an image, Semantic Segmentation lays the foundation for higher-level tasks like object detection, tracking, and activity recognition. This technique hinges on Deep Learning algorithms that can effectively learn patterns in vast quantities of data, thus enabling accurate pixel-wise classifications. Consequently, Semantic Segmentation is a pivotal component in the realm of Artificial Intelligence and Technology at large, contributing to advancements across diverse industries by offering unprecedented insights into visual content analysis.