Skin Cancer Classifier: Unable to find normal skin images












1















Summary:



I'm working with TensorFlow to build skin cancer classifier I have found many images for skin cancer with labels. My problem is I haven't found any images for normal skin or false skin cancer. I noticed all blogs referred to some skin cancer dataset but never normal skin images.



Questions:



How can the network know what is and what is not skin cancer?



If a network is trained only with types of cancer and i give a normal skin image will it predict one of the skin cancer types?



Thank you



One of the blogs:



https://medium.com/intech-conseil-expertise/detect-mole-cancer-with-your-smartphone-using-deep-learning-8afad1efde8a



PS:New to deep learning










share|improve this question



























    1















    Summary:



    I'm working with TensorFlow to build skin cancer classifier I have found many images for skin cancer with labels. My problem is I haven't found any images for normal skin or false skin cancer. I noticed all blogs referred to some skin cancer dataset but never normal skin images.



    Questions:



    How can the network know what is and what is not skin cancer?



    If a network is trained only with types of cancer and i give a normal skin image will it predict one of the skin cancer types?



    Thank you



    One of the blogs:



    https://medium.com/intech-conseil-expertise/detect-mole-cancer-with-your-smartphone-using-deep-learning-8afad1efde8a



    PS:New to deep learning










    share|improve this question

























      1












      1








      1








      Summary:



      I'm working with TensorFlow to build skin cancer classifier I have found many images for skin cancer with labels. My problem is I haven't found any images for normal skin or false skin cancer. I noticed all blogs referred to some skin cancer dataset but never normal skin images.



      Questions:



      How can the network know what is and what is not skin cancer?



      If a network is trained only with types of cancer and i give a normal skin image will it predict one of the skin cancer types?



      Thank you



      One of the blogs:



      https://medium.com/intech-conseil-expertise/detect-mole-cancer-with-your-smartphone-using-deep-learning-8afad1efde8a



      PS:New to deep learning










      share|improve this question














      Summary:



      I'm working with TensorFlow to build skin cancer classifier I have found many images for skin cancer with labels. My problem is I haven't found any images for normal skin or false skin cancer. I noticed all blogs referred to some skin cancer dataset but never normal skin images.



      Questions:



      How can the network know what is and what is not skin cancer?



      If a network is trained only with types of cancer and i give a normal skin image will it predict one of the skin cancer types?



      Thank you



      One of the blogs:



      https://medium.com/intech-conseil-expertise/detect-mole-cancer-with-your-smartphone-using-deep-learning-8afad1efde8a



      PS:New to deep learning







      neural-network deep-learning dataset conv-neural-network






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      asked Nov 24 '18 at 23:44









      HeRoXLeGenD1HeRoXLeGenD1

      124




      124
























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          That problem should be quite easy to resolve by pics of lots of healthy people pics!



          You can't perform supervised learning without a database of control images. You could redefine the question against the images that you have.



          If you can't do either you are stuck with unsupervised learning and your positive images will serve only to verify your unsupervised learning conclusions. You are hoping your unsupervised learning will yield two groups and if correct one of the group should map against your positive images. Then its solved without the control data set.



          If you can successfully map your positive images onto your output then the remainder becomes your control set for supervised learning, i.e. they become your training set.






          share|improve this answer



















          • 1





            Now I get the point of unsupervised learning. Thank you !

            – HeRoXLeGenD1
            Nov 25 '18 at 0:55











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          active

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          0














          That problem should be quite easy to resolve by pics of lots of healthy people pics!



          You can't perform supervised learning without a database of control images. You could redefine the question against the images that you have.



          If you can't do either you are stuck with unsupervised learning and your positive images will serve only to verify your unsupervised learning conclusions. You are hoping your unsupervised learning will yield two groups and if correct one of the group should map against your positive images. Then its solved without the control data set.



          If you can successfully map your positive images onto your output then the remainder becomes your control set for supervised learning, i.e. they become your training set.






          share|improve this answer



















          • 1





            Now I get the point of unsupervised learning. Thank you !

            – HeRoXLeGenD1
            Nov 25 '18 at 0:55
















          0














          That problem should be quite easy to resolve by pics of lots of healthy people pics!



          You can't perform supervised learning without a database of control images. You could redefine the question against the images that you have.



          If you can't do either you are stuck with unsupervised learning and your positive images will serve only to verify your unsupervised learning conclusions. You are hoping your unsupervised learning will yield two groups and if correct one of the group should map against your positive images. Then its solved without the control data set.



          If you can successfully map your positive images onto your output then the remainder becomes your control set for supervised learning, i.e. they become your training set.






          share|improve this answer



















          • 1





            Now I get the point of unsupervised learning. Thank you !

            – HeRoXLeGenD1
            Nov 25 '18 at 0:55














          0












          0








          0







          That problem should be quite easy to resolve by pics of lots of healthy people pics!



          You can't perform supervised learning without a database of control images. You could redefine the question against the images that you have.



          If you can't do either you are stuck with unsupervised learning and your positive images will serve only to verify your unsupervised learning conclusions. You are hoping your unsupervised learning will yield two groups and if correct one of the group should map against your positive images. Then its solved without the control data set.



          If you can successfully map your positive images onto your output then the remainder becomes your control set for supervised learning, i.e. they become your training set.






          share|improve this answer













          That problem should be quite easy to resolve by pics of lots of healthy people pics!



          You can't perform supervised learning without a database of control images. You could redefine the question against the images that you have.



          If you can't do either you are stuck with unsupervised learning and your positive images will serve only to verify your unsupervised learning conclusions. You are hoping your unsupervised learning will yield two groups and if correct one of the group should map against your positive images. Then its solved without the control data set.



          If you can successfully map your positive images onto your output then the remainder becomes your control set for supervised learning, i.e. they become your training set.







          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Nov 25 '18 at 0:37









          Michael G.Michael G.

          2351317




          2351317








          • 1





            Now I get the point of unsupervised learning. Thank you !

            – HeRoXLeGenD1
            Nov 25 '18 at 0:55














          • 1





            Now I get the point of unsupervised learning. Thank you !

            – HeRoXLeGenD1
            Nov 25 '18 at 0:55








          1




          1





          Now I get the point of unsupervised learning. Thank you !

          – HeRoXLeGenD1
          Nov 25 '18 at 0:55





          Now I get the point of unsupervised learning. Thank you !

          – HeRoXLeGenD1
          Nov 25 '18 at 0:55




















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