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Aa posted an Question

September 12, 2020 • 02:49 am

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IIT JAM
Geology (GG)

What is supervised classification and unsupervised classification ?

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Sajan sarthak

see the answer is attached
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nice explanation sir
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why their is need of tarining data and erros came in supervised classification ?
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Rahul kumar Best Answer

Supervised classification is based on the idea that a user can select sample pixels in an image that are representative of specific classes and then direct the image processing software to use these training sites as references for the classification of all other pixels in the image. Input classes are selected based on the knowledge of the user. The user also sets the bounds for how similar other pixels must be to group them together. Unsupervised classification is where the outcomes (groupings of pixels with common characteristics) are based on the software analysis of an image without the user providing sample classes. The computer uses techniques to determine which pixels are related and groups them into classes. Refer to the attached figure for advantages and disadvantages associated with supervised and unsupervised classification.
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which is more useful?
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It depends on the previous knowledge of the area. If the observer have the knowledge about the image area then he can choose the particular reference points (roads, river, vegetation etc.) in the image and can go for supervised classification. If the image area is completely unknown then it's impossible to decide the reference points and in such cases unsupervised classification is the only possible way.
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