Hello everyone, I am Azheng. Today, I am excited to introduce a “martial arts master”—PyTorch, a Python library that is like a dynamic neural network superhero! With it, you can navigate the world of neural networks with ease. 1. Getting to Know PyTorch Imagine PyTorch as a magical “workshop” that specializes in creating amazing tools … Read more
Alibaba Guide: Pedestrian re-identification refers to the task of accurately finding the same person in images from different cameras given a picture of that person from one camera. This technology holds significant research and practical application value, and has recently been widely applied in fields such as traffic and security, playing an important role in … Read more
Introduction Have you ever felt overwhelmed by the complexity of deep learning? Have you heard of the powerful tool known as Convolutional Neural Networks (CNN) but found it confusing? Don’t worry! This article will guide you step by step through the core concepts of CNN and teach you how to easily build and train a … Read more
Follow “Deep Learning Natural Language Processing” to learn and grow together! Bookmark us to get more valuable content first-hand. Author: Yun Bu Jian Link: https://blog.csdn.net/Walk_OnTheRoad/article/details/108048101 Editor: Wang Meng, City University of Macau (Deep Learning Community) This note is based on the key knowledge summary from the book “Introduction to Deep Learning”.. Continuing from the notes … Read more
Researchers from the South China University of Technology have published a paper that describes the mathematical principles of convolutional networks. This paper explains the operations and propagation processes of convolutional networks from a mathematical perspective.This paper is very helpful for understanding the mathematical essence of convolutional networks and assists readers in implementing convolutional networks “by … Read more
Introduction: Deep learning can be applied in various fields, and the shapes of deep neural networks vary according to different application scenarios. The common deep learning models mainly include Fully Connected (FC), Convolutional Neural Network (CNN), and Recurrent Neural Network (RNN). Each of these has its own characteristics and plays an important role in different … Read more
Link: https://www.zhihu.com/question/59532432/answer/1510340606 Editor: Deep Learning and Computer Vision Disclaimer: For academic sharing only, please delete if infringed Time domain convolution = frequency domain multiplication. Most of the computations in convolutional neural networks occur in the convolution part. How to think about convolutional neural networks from the perspective of the frequency domain? How to explain ResNet … Read more
In this blog, we will delve into the fascinating world of action recognition using the UCF101 dataset. Action recognition is a key task in computer vision, with applications ranging from surveillance to human-computer interaction. The UCF101 dataset serves as our playground for this exploration. Our goal is to build an action recognition model that combines … Read more
Author: Amber Original submission to SSD Fans, earn >= 100 CNY for articles. Since AlexNet won the ImageNet challenge in 2012, deep learning technology has been increasingly used in various fields of artificial intelligence. Among them, Convolutional Neural Networks (CNN) have excelled in image classification tasks. However, due to the high computational cost of CNNs, … Read more
In the field of artificial intelligence, Convolutional Neural Networks (CNN) have become essential tools for tasks such as image recognition and object detection. This article will guide you through the basic principles of CNNs, making it easy for you to get started with this powerful AI technology. 1. What is a Convolutional Neural Network? A … Read more