Image Segmentation - binary cross entropy indicates over-fitting, dice doesn't











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I encountered a problem which is difficult for me to explain:



enter image description here
I train a modified UNet variant with binary cross entropy and I plot the dice scores as well. This is how the result looks like. The distribution of the mask pixels in the training and the test set are different.



Can anyone elaborate why dice and BCE is not correlating at all in this case? Or what are potential reasons why the two are not correlating?



Thanks!






deep-learning







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    up vote
    -1
    down vote

    favorite












    I encountered a problem which is difficult for me to explain:



    enter image description here
    I train a modified UNet variant with binary cross entropy and I plot the dice scores as well. This is how the result looks like. The distribution of the mask pixels in the training and the test set are different.



    Can anyone elaborate why dice and BCE is not correlating at all in this case? Or what are potential reasons why the two are not correlating?



    Thanks!






    deep-learning







    share|improve this question
























      up vote
      -1
      down vote

      favorite









      up vote
      -1
      down vote

      favorite











      I encountered a problem which is difficult for me to explain:



      enter image description here
      I train a modified UNet variant with binary cross entropy and I plot the dice scores as well. This is how the result looks like. The distribution of the mask pixels in the training and the test set are different.



      Can anyone elaborate why dice and BCE is not correlating at all in this case? Or what are potential reasons why the two are not correlating?



      Thanks!






      deep-learning







      share|improve this question













      I encountered a problem which is difficult for me to explain:



      enter image description here
      I train a modified UNet variant with binary cross entropy and I plot the dice scores as well. This is how the result looks like. The distribution of the mask pixels in the training and the test set are different.



      Can anyone elaborate why dice and BCE is not correlating at all in this case? Or what are potential reasons why the two are not correlating?



      Thanks!






      deep-learning




      deep-learning






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 11 at 14:54









      Styp

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