Implementation of EDSR, ESPCN, LAPSRN, SRCNN, SRGAN and WDSR for single image super-resolution (SISR) based on Tensorflow 2.x for CMU's 10-707 Advanced Deep Learning Final Project
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Updated
Apr 29, 2022 - Jupyter Notebook
Implementation of EDSR, ESPCN, LAPSRN, SRCNN, SRGAN and WDSR for single image super-resolution (SISR) based on Tensorflow 2.x for CMU's 10-707 Advanced Deep Learning Final Project
Image Classification
This project is about the fundamentals of super-resolution artificial intelligence, specifically centered on the Enhanced Deep Super-Resolution (EDSR) technique. EDSR is used to improve image quality and resolution. The project includes a practical example demonstrating how a basic EDSR model works in enhancing images.
PyTorch implementation of SRCNN and EDSR neural networks for Super Resolution Single Frame tasks
Martialis - Optical Character Recognition Discord Bot running on Google's Tesseract OCR Engine
Research on AI Technology for the Efficient Real-Time Object Detection using super-resolution.
This is an Image Enhancement project which uses EDSR, WDSR, and SRGAN methods to increase the resolution of an image while also improving the details significantly.
Deep.Imager - A Python based app powered by Streamlit! Upscales images using mathematical convolutions and Deep Learning without change/loss in input sharpness
EDSR with depthwise separable convolution
A simple image upscaler application using EDSR, ESPCN, FSRCNN, and LapSRN models
Super Resolution using EDSR. Enhanced Deep Residual Networks for Single Image Super-Resolution (EDSR) model trained to convert a Low-Resolution image to a Super-Resolution image.
Can we perform face hallucination using limited set of unaligned pairs?
single image super resolution
This repository is an implementation of EDSR model implemented in PyTorch
Tensorflow Implementation of enhanced deep super-resolution network (EDSR) and Super Resolution Generative Adversarial Networks(SRGAN) Paper
Super-Resolution models implemented in PyTorch Lightning
ERNet: Segmentation of Endoplasmic Reticulum microscopy images using modified CNN-based image restoration models.
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