Image super resolution using with Deep Convolutional Neural Networks
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Updated
Jul 15, 2023 - Jupyter Notebook
Image super resolution using with Deep Convolutional Neural Networks
IKC: Blind Super-Resolution With Iterative Kernel Correction
HiRN: Hierarchical Recurrent Neural Network for Video Super-Resolution (VSR) using Two-Stage Feature Evolution - Official Repository (Applied Soft Computing)
Image Super-Resolution Using ESRGAN
Pytorch implementation of "Activating More Pixels Sparsely: A Structural Similarity-Inspired Unrolling Framework for Lightweight Image Super-Resolution"
ESRGAN
A PyTorch implementation of ESRGAN. Additionally, a weight file trained for 200 epochs will be provided.
Group-based Bi-Directional Recurrent Wavelet Neural Network for Efficient Video Super-Resolution (VSR) - Official Repository (Pattern Recognition Letters)
This is the repository of the code related to Ruben Moyas's MSc in Data Science Master's Thesis.
The experimental implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" ( SRGAN )
Official implementation of "MAML-SR: Self-Adaptive Super-Resolution Networks via Multi-scale Optimized Attention-aware Meta-Learning" (PRL'23)
Functional interpolation to create a more meaningful interpolation than bilinear or bicubic methods.
Convert multiple LR images to single HR image.
This is a python package to perform progressive refinement method for sparse recovery (PRIS)
Capstone project for a course on machine learning and deep learning - Single Image Super Resolution
Super enhancement of Hi-C contact map resolutions
Számítógépes képfeldolgozás
ZSSR (Zero-Shot Super Resolution) code by PyTorch.
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