Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
-
Updated
Feb 22, 2024 - Python
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Tensorflow implementation of the SRGAN algorithm for single image super-resolution
ImageNet pre-trained models with batch normalization for the Caffe framework
The VGG16 and VGG19 networks in caffe with jupyter notebook
VggML (ICPR 2018, Beijing)
VGG16 Net implementation from PyTorch Examples scripts for ImageNet dataset
Multiclass image classification using Convolutional Neural Network
A program that can add an artistic touch to any image.
Project to find one of 9 pre-trained emotions on given photo, video or webcam-stream
Pre-trained VGG-Net Model for image classification using tensorflow
Generative Adversarial Network for single image super-resolution in high content screening microscopy images
Tensorflow implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" (Ledig et al. 2017)
Implementation of 'merge' architecture for generating image captions from paper "What is the Role of Recurrent Neural Networks (RNNs) in an Image Caption Generator?" using Keras. Dataset used is Flickr8k available on Kaggle.
Neural Style implementation in PyTorch! 🎨
Implementation of style transfer by tensorflow, for detail please see the paper "Image Style Transfer Using Convolutional Neural Networks"(CVPR2016)
Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation
This repo includes classifier trained to distinct 7 type of skin lesions
Add a description, image, and links to the vgg19 topic page so that developers can more easily learn about it.
To associate your repository with the vgg19 topic, visit your repo's landing page and select "manage topics."