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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 an entire image (e.g., distinguishing between a cat and a dog at the pixel level). Shrini illustrates this with an example of a rock sample to show how different minerals are identified through segmentation. He critiques the traditional accuracy metric, noting its limitations, particularly in cases of class imbalance that often occur in multi-class scenarios, making IoU a more reliable evaluation method for semantic segmentation.
