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In this video, Shrini discusses the best approach to evaluate semantic segmentation using the intersection over union (IoU) method. Semantic segmentation involves classifying individual pixels instead of labeling an entire image, allowing for a more detailed understanding, such as identifying pixels belonging to a cat or a dog. Shrini highlights a common issue with using accuracy as a metric; it can be misleading in cases of class imbalance often encountered in multi-class problems. As such, IoU is presented as a more reliable metric for evaluating segmentation performance.