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In this video, Shrini discusses the best method for evaluating semantic segmentation using the intersection over union (IoU) approach. He explains that semantic segmentation involves classifying individual pixels instead of labeling entire images, as demonstrated with a sample of rock minerals. Shrini highlights the limitation of using accuracy as a performance metric, especially in multi-class problems with class imbalance, which can lead to misleading results. Instead, he advocates for the IoU method, which provides a more reliable evaluation of semantic segmentation performance.
