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In this tutorial, Shrini discusses the evaluation of semantic segmentation using the intersection over union (IoU) approach. Semantic segmentation involves classifying individual pixels instead of classifying an entire image, as illustrated with a sample of a rock showing different minerals. Shrini highlights that accuracy, commonly used in metrics, is not ideal for semantic segmentation due to class imbalance, especially in multi-class scenarios encountered in real-life applications. The tutorial aims to provide better evaluation methodologies suited for semantic segmentation challenges.