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In this video, Shrini discusses how to effectively evaluate semantic segmentation using the Intersection over Union (IoU) approach. He defines semantic segmentation as the process of classifying individual pixels within an image, rather than categorizing the entire image, exemplified through a rock sample showcasing different minerals. Shrini highlights the limitations of using accuracy as a metric for evaluation, especially in cases of class imbalance in multi-class problems, where traditional accuracy measures may not provide an accurate reflection of performance.