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About Dice Loss #28

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nini0919 opened this issue Jul 14, 2023 · 2 comments
Open

About Dice Loss #28

nini0919 opened this issue Jul 14, 2023 · 2 comments

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@nini0919
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Hello, author! Thank you for contributing an influential paper to the field of res. I have a small question to ask you regarding your statement on April 13th, 2023: "Using the Dice loss instead of the cross-entropy loss can improve results. Will add code and release weights later when getting a chance." Could you please provide the calculation code for the dice loss? Thank you, good luck!

@yz93
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yz93 commented Jul 14, 2023

Hello! Hopefully I get time to do this soon. Thanks for your interest in the work.

@nini0919
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Thank you for your patient answer. We are looking forward to your release of the code related to Dice loss.

Besides, I found the dimension of the network output tensor is [batch_size, 2, 480, 480], and I think the second dimension represents the classes of the pixel, 0 is background and 1 is foreground. Therefore, I want to ask you what is the meaning of 'multi-class' for multi-class Dice loss. Do you mean that "multi-class" refers to foreground and background classes?Thank you, good luck!

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