Deep CNN Autoencoder - Denoising Image | Deep Learning | Python

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⭐️ Content Description ⭐️
In this video, I have explained on how to use autoencoder to remove noises in the image. This application will be very helpful in image processing. The autoencoder is built using deep cnn model to remove noise from mnist images.

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Hey everyone. In model prediction, use xtest_noisy instead of xtest. The updated notebook is also available in GitHub with results. Happy Learning!!!!

HackersRealm

At the end, you make a prediction on the original data. For prediction you need to use x_test_noisy instead of x_test. So, in the results part, you are just showing us a noisy and original image. Your model is unlikely to have learned anything (look at the losses in each epoch). If I'm wrong please correct me as I'm new to this topic.

milanabegantsova

If we use adadelta or adamax or adagraf instead of adam optimiser.. what will be the result ?

ksalve

Is the denoiser only good at denoising images actually containing a digit ? (since digits is the only trained data)
What would happen if you would input something else (eg: letter or other symbols). Would it try to morphe it to the closest digit or would it be able to denoise it properly ?

Tigrou

How to use mean squared error instead of binary cross entropy in loss function

smritisingh

give me code for
how to check accuracy
image similarity in code

korrarakesh

Deep CNN Autoencoder - Denoising Image | Deep Learning | Python

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