Use a Denoising Autoencoder (DAE) to learn clean image representations from noisy inputs in an unsupervised manner. Here is the code snippet you can refer to:

In the above code, we are using the following key points:
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Learns to reconstruct clean images without labeled pairs.
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Trains using only noisy input as supervision.
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Robust to different noise levels.
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Lightweight and effective for pre-processing tasks
Denoising autoencoders learn latent representations that filter noise from input data, hence enabling effective unsupervised image denoising using generative modeling techniques.