Click on the above “Visual Learning for Beginners”, select to add “Starred” or “Top” Important information delivered at the first time Source: WeChat Official Account Machine Heart Authorized Can GAN systematically control the style of the generated images? Do you understand your style? Most GAN models do not understand. So, can GAN systematically control the … Read more
Original Title: An Intuitive Introduction to Generative Adversarial Networks Authors: Keshav Dhandhania, Arash Delijani Translation: Shen Libin Proofreading: He Zhonghua This article is about 4000 words and is recommended to be read in 10 minutes. The article introduces the GAN model through the problem of image generation, discusses the mathematical principles and training process of … Read more
Click the “MLNLP” above to select the “star” public account Heavyweight content delivered promptly Source: Learning Notes of Qianmeng “ This article mainly introduces the recent developments and representative works of GAN (Generative Adversarial Networks) in distribution discrepancy measurement, IPM and regularization, dual learning, conditioning and control, resolution enhancement, evaluation metrics, etc. It is hoped … Read more
Recently, Associate Professor Yi Shi’s team from the School of Mechanical and Electrical Engineering at Chengdu University of Technology conducted research on the issue of edge and texture blurring in fused images of infrared and visible light. The related paper titled “Infrared and Visible Image Fusion Based on Blur Suppression Generative Adversarial Network” was published … Read more
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
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
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
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
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
