despoisj/ConvolutionalAutoencoder
Quick and dirty example of the application of convolutional autoencoders in Keras/Tensorflow
This example helps you understand how convolutional autoencoders can process images. It takes an image as input, compresses it into a smaller representation, and then reconstructs it, showing how well the original image can be preserved after compression and decompression. This is useful for anyone new to deep learning or image processing who wants to see autoencoders in action.
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Use this if you are learning about neural networks and want a straightforward illustration of how convolutional autoencoders work with image data.
Not ideal if you need a production-ready solution for image compression or a highly optimized autoencoder for complex research tasks.
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Language
Python
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Last pushed
Jul 26, 2021
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