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In this tutorial, Shrini discusses the optimal method for evaluating semantic segmentation, focusing on the Intersection Over Union (IoU) approach. He explains semantic segmentation as the process of classifying individual pixels in an image, as opposed to merely classifying the entire image. Using an example of a rock sample with various minerals, he illustrates the concept. Shrini also points out the limitations of using accuracy as a metric for evaluation, especially in cases of class imbalance that arise in multi-class scenarios. He mentions that relying solely on accuracy can be misleading in such situations.