Building CNN Networks with Object-Oriented Programming | PyTorch Series

Building CNN Networks with Object-Oriented Programming | PyTorch Series

Click the “Beginner’s Visual Learning” above to choose to add “Star” or “Pinned“. Important content delivered promptly. From a high-level perspective of our deep learning project, we have prepared the data, and now we are ready to build our model. Prepare Data Build Model Train Model Analyze Model Results When we talk about the model, … Read more

Explaining CNNs From the Frequency Domain Perspective

Explaining CNNs From the Frequency Domain Perspective

Click on “Computer Vision Life” above, and select “Star” Quickly get the latest insights This article is compiled from Zhihu Q&A. If there is any infringement, please delete it. Editor丨Extreme City Platform Viewpoint 1 Author丨Ruo Yu I think the most enlightening work for me is by Xu Zhiqin from Shanghai Jiao Tong University. https://ins.sjtu.edu.cn/people/xuzhiqin/fprinciple/index.html His … Read more

Deep Dive Into VGGNet: A Classic CNN Architecture

Deep Dive Into VGGNet: A Classic CNN Architecture

In 2014, the Visual Geometry Group at the University of Oxford and Google DeepMind developed a new convolutional neural network called VGGNet. VGGNet is a deeper deep convolutional neural network than AlexNet, and this model achieved second place in the 2014 ILSVRC competition, with GoogLeNet taking first place (which we will introduce later). Paper: Very … Read more

Bold and Innovative Neural Network Structures in CNN

Bold and Innovative Neural Network Structures in CNN

Click the above “AI Youdao” and select “Star” public account Heavyweight content delivered immediately Editor: Yi Zhen https://www.zhihu.com/question/337470480 This article is for academic sharing only. If there is an infringement, it will be deleted. Reports on machine learning algorithms and natural language processing What Bold and Innovative Neural Network Structures Exist in Convolutional Neural Networks? … Read more

RNN Transformation Mechanism and Practical Applications

RNN Transformation Mechanism and Practical Applications

Follow Hui Kuo Technology to learn more about technology knowledge Hello everyone, I am Liu Zenghui! Today we will continue the series of lectures on artificial intelligence neural networks, focusing on the transformation mechanism and practical applications of RNNs, exploring how they are widely used in various fields! Transformation Mechanism of RNN In the previous … Read more

Understanding the Mathematical Principles Behind RNNs

Understanding the Mathematical Principles Behind RNNs

0Introduction Nowadays, discussions about machine learning, deep learning, and artificial neural networks are becoming more and more prevalent. However, programmers often just want to use these magical frameworks without wanting to know how they actually work behind the scenes. But if we could grasp these underlying principles, wouldn’t it be better for us to use … Read more

When RNN Meets Reinforcement Learning: Building General Models for Space

When RNN Meets Reinforcement Learning: Building General Models for Space

You may be familiar with reinforcement learning, and you may also know about RNNs. What sparks can these two relatively complex concepts in the world of machine learning create together? Let me share a few thoughts. Before discussing RNNs, let’s first talk about reinforcement learning. Reinforcement learning is gaining increasing attention; its importance can be … Read more

Four Structures of RNN

Four Structures of RNN

Starting the Journey of RNN, Commonly Known Four Structures of RNN One to One: This is the traditional application of neural networks, usually used for simple input to output tasks. For example, in image classification, the network receives an image as input and identifies the category of the object represented in the image. Specifically, suppose … Read more

Do RNN and LSTM Have Long-Term Memory?

Do RNN and LSTM Have Long-Term Memory?

This article introduces the ICML 2020 paper “Do RNN and LSTM have Long Memory?“. The authors of the paper are from Huawei Noah’s Ark Lab and the University of Hong Kong.. Author | Noah’s Ark Lab Editor | Cong Mo Paper link: https://arxiv.org/abs/2006.03860 1 Introduction To overcome the difficulties of Recurrent Neural Networks (RNNs) in … Read more