Code Organization

Reconstructing Faces from fMRI Patterns Using Deep Generative Neural Networks

by

This article is a work by Professor Rufin VanRullen from the Université de Toulouse, published in Communications Biology in 2019, titled “Reconstructing faces from fMRI patterns using deep generative neural networks“. DOI: 10.1038/s42003-019-0438-y. Abstract Despite reliably decoding different categories from fMRI brain responses, distinguishing visually similar inputs, such as different faces, has proven more challenging. … Read more

Research Progress and Trends of Generative Adversarial Networks

by
Research Progress and Trends of Generative Adversarial Networks

CCF published a new issue of the “China Computer Science and Technology Development Report” in October 2018, detailing the research progress in ten directions, including the deep integration of AI and system software. We will share the highlights of the report in installments. Please join CCF and log in to the CCF digital library to … Read more

Mathematical Principles of GAN

by
Mathematical Principles of GAN

Mathematical Derivation of GAN Author: Sherlock Source: Machine Learning Algorithms and Natural Language Processing Previously, we discussed the basic idea of GAN. Recently, I reviewed some GAN papers and happened to watch a course by Professor Li Hongyi, finding the mathematical derivation quite interesting, so I decided to write it down for future reference. First, … Read more

CycleGAN Image Processing Tool for Style Transfer

by
CycleGAN Image Processing Tool for Style Transfer

1. Introduction to GAN “Foodie, food spirit, foodies are the best of people”. This GAN foodie is not the same as that foodie. The GAN we are going to discuss is the Generative Adversarial Network proposed by Goodfellow in 2014. So what is so magical about GAN? Conventional deep learning tasks such as image classification, … Read more

A Survey of 193 GANs for Image Super-Resolution

by
A Survey of 193 GANs for Image Super-Resolution

Follow our public account to discover the beauty of CV technology This article shares a recent literature review on super-resolution titled ‘Generative Adversarial Networks for Image Super-Resolution: A Survey’. It discusses the performance, advantages, disadvantages, complexity, challenges, and potential research points of 193 related papers. Specific information is as follows: Authors: Tian Chunwei, Zhang Xuan … Read more

Overview of GAN Models and Medical Image Fusion Applications

by
Overview of GAN Models and Medical Image Fusion Applications

The “Outcome Overview” series of articles aims to disseminate important results from conferences and journals in the field of image graphics, allowing readers to quickly understand relevant academic dynamics in their native language through short articles. We welcome your attention and submissions~ ◆ ◆ ◆ ◆ GAN Review: Models and Medical Image Fusion Applications Zhou … Read more

Understanding GAN Limitations in Image Synthesis

by
Understanding GAN Limitations in Image Synthesis

Source: Machine Heart (ID: almosthuman2014) This article contains 3890 words and 23 images, recommended reading time is 10 minutes. This article introduces how to avoid omissions when using Generative Adversarial Networks (GAN) for image synthesis to create a higher quality image generator, including related papers, code, and data. [Introduction] Generative Adversarial Networks (GAN) can now … Read more

ArmGAN: Adversarial Representation Learning for Network Embedding

by
ArmGAN: Adversarial Representation Learning for Network Embedding

Network embedding aims to learn low-dimensional representations of nodes in a network, which can be used for many downstream network analysis tasks. Recently, many network embedding methods based on Generative Adversarial Networks (GANs) have been proposed. However, GAN-based methods mainly face two challenges: (1) Existing GAN-based methods often use GANs to learn Gaussian distributions as … Read more

Implementing GAN on Keras: Building an Image Deblurring Application

by
Implementing GAN on Keras: Building an Image Deblurring Application

Click on the above “Beginner’s Visual Learning” to select “Star” or “Pin” Heavyweight content delivered first hand In 2014, Ian Goodfellow proposed Generative Adversarial Networks (GANs), which have become one of the hottest directions in deep learning today. This article will focus on how to use Keras to apply GAN to the task of image … Read more

Introduction to TensorFlow: Generative Adversarial Networks

by

Currently, in the field of deep learning, Generative Adversarial Networks (GANs) are very popular, bringing us an incredible direction in this field. Today, I will share how to use GANs to generate images (Mnist and cartoon faces). 1. How GANs Came to Be It is said in academia that the founder of GANs, Ian Goodfellow, … Read more