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Enhancing the video quality using super resolution and deep neural networks

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Super Resolution for Improving Video Quality

A Keras and Tensorflow implementation of super resolution using deep neural networks is proposed. The architecture is shown below.

Network Architecture

Training

  • We divide the video temporal consecutive segments of 1 second duration
  • We downsample the images of each segment and feed both downsampled and original image for training
  • Each video segment has its own model (we called it as a micro-model because it is trained on a little data of 30 images)
  • We overfit the model intentionally as there is no test phase

Prerequisites

  • Python3
  • Tensorflow
  • Keras
  • Jupyter Notebook (optional)

Authors

Pranjal Sahu, Mallesham Dasari

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Enhancing the video quality using super resolution and deep neural networks

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