Source: DeepHub IMBA This article is about 3800 words, and it is recommended to read in 5 minutes. Since the release of diffusion models, the attention and papers on GANs have decreased significantly, but some ideas within them are still worth understanding and learning. Therefore, in this article, we will implement SN-GAN using PyTorch. Spectral … Read more
The invention of the vacuum tube was a significant driving force in the development of the electronics industry. However, after World War II, the need for a large number of discrete components significantly increased the complexity and power consumption of devices, while their performance continuously declined. One example is the Boeing B-29, which consisted of … Read more
Nature Communications 2020 Jan 9 IF: 17.694 Introduction: GAN includes a generator that outputs realistic silicon-generated samples. This is achieved through a neural network that learns to transform a simple low-dimensional distribution into a high-dimensional distribution, which is indistinguishable from the actual training distribution. In this paper, the authors establish a single-cell GAN (scGAN) to … Read more
Welcome to follow and receive learning materials. After selecting from the public account, you can receive daily updates. Plot In episode 7 of Qing Yu Nian 2, aside from the queen, there is a question of “who exactly is this woman in the painting”. Fan Xian also discovers the faceless woman in the prince’s painting, … Read more
Xiao Xiao Yu Yang from Aofeisi Reported | Quantum Bit When it comes to computer vision, CNN is indispensable. But what do convolution, pooling, and Softmax actually look like, and how are they interconnected? Imagining it from code can be a bit chilling. So, someone simply used Unity to create a complete 3D visualization. It’s … Read more
Click on the above “Beginner’s Guide to Vision”, select to add “Bookmark” or “Pin” Important content delivered immediately From | Blog Garden Author | CZiFan Background Geoffrey Hinton is one of the pioneers of deep learning and the inventor of classic algorithms for neural networks like backpropagation. He and his team proposed a novel neural … Read more
Click on the above “Beginner Learning Vision” to select “Star Mark” or “Top“ Important content delivered immediately 01 Paper Overview Paper Title: “How much Position Information Do Convolutional Neural Networks Encode? “ Paper Link: https://openreview.net/forum?id=rJeB36NKvB This article explains how CNNs learn the absolute position information within images. The article comes from Canadian scholars and is … Read more
Click on the above“Learn Visuals” to selectStar or “Top” Heavyweight content, delivered first Background Introduction In common convolutional neural networks, sampling is almost everywhere, previously max pooling, now strided convolution. Taking the VGG network as an example, it uses quite a bit of max pooling. The input side is on the left (the bottom has … Read more
Author: zzq https://zhuanlan.zhihu.com/p/68411179 This article is authorized, and unauthorized reproduction is not allowed. Introduction to Basic Components of CNN 1. Local Receptive Field In images, the connections between local pixels are relatively tight, while the connections between distant pixels are weaker. Therefore, each neuron does not need to perceive the entire image globally; it only … Read more
Click on the above “Beginners Learn Vision”, select to add “Star” or “Top” Important content delivered at the first time Convolutional Neural Networks (CNN) are fundamental knowledge in deep learning. This article provides a detailed interpretation of the basic principles of CNN and common CNN architectures, and introduces the process of building deep networks with … Read more