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In this video, Shrini discusses the best approach to evaluate semantic segmentation, focusing on the intersection over union (IoU) method. He explains that semantic segmentation involves classifying individual pixels rather than labeling entire images, using the example of identifying minerals in a rock. Shrini highlights the limitations of using accuracy as a metric for evaluation, particularly in cases of class imbalance that commonly occur in multi-class problems. He emphasizes that accuracy may not provide a reliable assessment of performance in such scenarios.