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In this video, Shrini discusses the best way to evaluate semantic segmentation using the intersection over union (IoU) approach. Semantic segmentation involves classifying individual pixels in an image, rather than just labeling the entire image as a category. For example, it differentiates between pixels that belong to a cat or a dog, or, as shown in the video, identifies different minerals in a rock sample. Shrini explains that while accuracy is commonly used in classification, it is not effective for semantic segmentation, especially in cases of class imbalance that occur in multi-class problems in real-world scenarios.
