Source: AI Algorithms and Image Processing This article is about 4300 words, recommended reading time is 8 minutes. A detailed interpretation of the stable diffusion paper, you will understand it after reading this article! 1. Introduction (Can Be Skipped) Hello, everyone! I am Tian-Feng. Today, I will introduce some principles of stable diffusion in an … Read more
Deepfake vs Anti-Deepfake: A Long-Term Cat and Mouse Game. Compiled by | Xinyuan Edited by | Moying The following report from Zhiyuan on June 18 asks, can you spot any issues with the photos of these people? These smiling individuals are all fake, generated by a well-known AI model called StyleGAN, and do not exist … Read more
This article is an original piece from the WeChat public account “Dahua Imaging” and the Zhihu column “All In Camera”. Please cite the source for reproduction. Join the Dahua Imaging Reader QQ Group 2: 833282006. Dahua Imaging Technology Forum: ww.dahuachengxiang.com. Please add zxzombie to the WeChat group first. New teaching videos on “Image Sensor Technology … Read more
[Image] Convolutional Neural Networks (CNN), one of the classic forms of deep learning neural networks, is named for its computation process that includes convolution operations. CNNs extract local features from image data using convolutional layers, followed by pooling layers (Pooling Lay…
Brothers, today we are going to talk about a particularly “high-end” but actually very practical and interesting technology – Convolutional Neural Networks (CNN). Don’t be afraid, the name sounds quite intimidating, but actually, if we chat in plain language, you will find that, hey, this thing is not that difficult! First, we need to understand … Read more
Using classic CNN methods to build an automatic extraction model for road elements in Guiyang She Zuoming, Shen Yongzhi, Song Jianhong, Xiang Yuchen Guiyang Surveying and Mapping Institute, Guiyang, Guizhou 550000 Keywords: CNN, Deep Learning, Road Extraction, Remote Sensing Interpretation Citation format: She Zuoming, Shen Yongzhi, Song Jianhong, et al. Using classic CNN methods to … Read more
✅Author Bio: A Matlab simulation developer passionate about research, skilled in data processing, modeling simulation, program design, complete code acquisition, paper reproduction, and scientific simulation. 🍎Personal Homepage:Matlab Research Studio 🍊Personal Motto: Seek knowledge through inquiry; feel free to message me for help. 🔥 Content Introduction Abstract: Respiratory motion in medical imaging is a critical factor … Read more
GiantPandaCV Introduction: This series has not been updated for several months, and we will continue to explore the papers in this direction. In 2019 and 2020, many studies on Attention emerged. This paper, SA-Net: Shuffle Attention for Deep Convolutional Neural Networks, published in ICASSP 21, inherits the design concept of SGE while introducing Channel Shuffle, … Read more
[Python Practical] Image Recognition Secrets: Master AI as Your Assistant! Hello everyone, I am Deep Learning Engineer Xiao K! Do you remember the excitement of implementing image recognition with Python for the first time? A simple piece of code can make computers “understand” images, it’s simply magical! Today, let’s explore the wonderful world of image … Read more
Introduction to Image Recognition: OpenCV Basics Today, I will introduce a revolutionary Python library in the field of computer vision—OpenCV. Whether you are a novice in image processing or an expert in computer vision, OpenCV is an indispensable assistant. Basic Introduction and Core Features OpenCV (Open Source Computer Vision Library) is a powerful open-source computer … Read more