Skin Cancer Classifier: Unable to find normal skin images
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
asked Nov 24 '18 at 23:44
HeRoXLeGenD1HeRoXLeGenD1
104
add a comment |
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
asked Nov 24 '18 at 23:44
HeRoXLeGenD1HeRoXLeGenD1
104
add a comment |
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
asked Nov 24 '18 at 23:44
HeRoXLeGenD1HeRoXLeGenD1
104
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
neural-network deep-learning dataset conv-neural-network
asked Nov 24 '18 at 23:44
HeRoXLeGenD1HeRoXLeGenD1
104
asked Nov 24 '18 at 23:44
HeRoXLeGenD1HeRoXLeGenD1
104
asked Nov 24 '18 at 23:44
HeRoXLeGenD1HeRoXLeGenD1
104
asked Nov 24 '18 at 23:44
HeRoXLeGenD1HeRoXLeGenD1
104
asked Nov 24 '18 at 23:44
HeRoXLeGenD1HeRoXLeGenD1
104
104
add a comment |
add a comment |
1 Answer
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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.
answered Nov 25 '18 at 0:37
Michael G.Michael G.
2231316
1
Now I get the point of unsupervised learning. Thank you !
– HeRoXLeGenD1
Nov 25 '18 at 0:55
add a comment |
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1 Answer
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active
oldest
votes
1 Answer
1
active
oldest
votes
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active
oldest
votes
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.
answered Nov 25 '18 at 0:37
Michael G.Michael G.
2231316
1
Now I get the point of unsupervised learning. Thank you !
– HeRoXLeGenD1
Nov 25 '18 at 0:55
add a comment |
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.
answered Nov 25 '18 at 0:37
Michael G.Michael G.
2231316
1
Now I get the point of unsupervised learning. Thank you !
– HeRoXLeGenD1
Nov 25 '18 at 0:55
add a comment |
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.
answered Nov 25 '18 at 0:37
Michael G.Michael G.
2231316
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.
answered Nov 25 '18 at 0:37
Michael G.Michael G.
2231316
answered Nov 25 '18 at 0:37
Michael G.Michael G.
2231316
answered Nov 25 '18 at 0:37
Michael G.Michael G.
2231316
answered Nov 25 '18 at 0:37
Michael G.Michael G.
2231316
2231316
1
Now I get the point of unsupervised learning. Thank you !
– HeRoXLeGenD1
Nov 25 '18 at 0:55
add a comment |
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
add a comment |
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