The softmax function is a mathematical function that converts a vector of raw scores (logits) into probabilities, ensuring that the output values are between 0 and 1 and sum to 1. This function is particularly useful in multi-class classification problems, including tasks such as image segmentation and classification where it helps in determining the likelihood of each class for a given input.
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