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## Notes
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* This model is a trained version of the Keras Tutorial [Image Super Resolution](https://keras.io/examples/vision/super_resolution_sub_pixel/)
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* The model has been trained on inputs of dimension 100x100 and outputs images of 300x300.
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## Notes
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* This model is a trained version of the Keras Tutorial [Image Super Resolution](https://keras.io/examples/vision/super_resolution_sub_pixel/)
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* The model has been trained on inputs of dimension 100x100 and outputs images of 300x300.
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[Link to a pyimagesearch](https://www.pyimagesearch.com/2021/09/27/pixel-shuffle-super-resolution-with-tensorflow-keras-and-deep-learning/) tutorial I worked on, where we have used Residual blocks along with the Efficient sub pixel net.
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