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

VggML (ICPR 2018, Beijing)

A program that can add an artistic touch to any image.

VGG16 Net implementation from PyTorch Examples scripts for ImageNet dataset

Multiclass image classification using Convolutional Neural Network

Neural Style implementation in PyTorch! :art:

Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation

Transferring the style of one image to the contents of another image, using PyTorch and VGG19.

Generative Adversarial Network for single image super-resolution in high content screening microscopy images

Implementation of style transfer by tensorflow, for detail please see the paper "Image Style Transfer Using Convolutional Neural Networks"(CVPR2016)

The VGG16 and VGG19 networks in caffe with jupyter notebook

Tensorflow implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" (Ledig et al. 2017)

Implementation of the paper : Deep image analogy

Pre-trained VGG-Net Model for image classification using tensorflow

No description provided.

Fast and Accurate User constrained Thumbnail Generation using Adaptive Convolutions. | ICASSP 2019 [ORAL]

Optimal deep texture generation and style transfer based on Eric Risser's paper

Multi-Sensor Image (infrared and visible) Fusion using deep learning framework, Principal Component Analysis, Discrete Wavelet Transform

使用pytorch，构建VGG19网络结构，对CIFAR10数据集进行分类

Deepdream experiment implemented using Keras and VGG19 convnet

In this repository you will find everything you need to know about Convolutional Neural Network, and how to implement the most famous CNN architectures in both Keras and PyTorch. (I'm working on implementing those Architectures using MxNet and Caffe)

Multi-Sensor Image (infrared and visible) Fusion using deep learning framework, Principal Component Analysis, Discrete Wavelet Transform

This code mainly implement the paper ' Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization ' by TensorFlow

Deep Learning course final project. 12th semester.

📜 A Novel Facial Emotion Recognition Model Using Segmentation VGG-19 Architecture

A Multi-modal Framework for Sentimental Analysis of Meme

This project presents a fingerprint matching system utilizing deep learning. It features multiple models, including VGG-based, SENet, CBAM, Self-Attention, and Dual-Attention architectures. Pre-trained MobileNet models with Self-Attention and SENet are also included. A web application allows for easy demonstration of the model's capabilities.

Models Supported: VGG11, VGG13, VGG16, VGG16_v2, VGG19 (1D and 2D versions with DEMO for Classification and Regression).