Click on the above“Learning Visuals for Beginners” to choose to addStar Mark or “Pin to Top” Important content delivered immediately The convolutional neural network is a deep network structure mainly composed of convolutional layers. The network structure includes convolutional layers, activation layers, BN layers, pooling layers, FC layers, loss layers, etc. The convolution operation is … Read more
0 Introduction Over the past few days, I have been watching some videos and reading blog posts about Convolutional Neural Networks (CNNs). I have organized the useful knowledge and content that I found helpful here, to clarify the logic and deepen my understanding. I can easily refer back to this in the future, ensuring it … Read more
Originally from Zhiyuan Community [Column: Key Issues]In recent years, we have witnessed increasingly powerful neural network models, such as AlexNet, VGG, GoogleNet, ResNet, DenseNet, and the recently popular Transformer. The processes used by these neural networks can be summarized as follows: 1) Fixed network architecture, initializing network parameters; 2) Training phase: optimizing network parameters on … Read more
Click on "Xiaobai Learns Vision" above, choose to add "Star" or "Top" Heavy content delivered at the first time Author: Piotr Skalski Source: AI Youdao @ WeChat Official Account Translation: Tongye (Sun Yat-sen University), had_in (University of Electronic Science and Technology) Introduction This article adopts an image presentation approach to help everyone understand the related … Read more
The hottest technology right now is definitely artificial intelligence. The underlying model of artificial intelligence is the “neural network”. Many complex applications (like pattern recognition, automatic control) and advanced models (like deep learning) are based on it. To learn artificial intelligence, one must start with it. What is a neural network? It seems that there … Read more
Source: Machine Vision Knowledge Recommender This article is approximately 11,000 words long and is recommended for a reading time of 10+ minutes. This article will introduce deep learning technology, neural networks, convolutional neural networks, and their applications in related fields. In today’s internet era, the intricate big data and network environment pose significant challenges to … Read more
Madio.net Mathematics China ///Editor: Only tulips’ garden Neural networks are a clever combination of linear and nonlinear modules. When we wisely choose and connect them, we have a powerful tool to approximate any mathematical function. For example, using nonlinear decision boundaries for classification. The backpropagation technique is responsible for updating the trainable parameters. Although it … Read more
Click the above“Beginner Learn Vision”, choose to addStar or “Top” Important content delivered in real-time The first convolutional neural network was proposed by Alexander Waibel in 1987, known as the Time Delay Neural Network (TDNN) [5]. TDNN is a convolutional neural network applied to speech recognition problems. It uses FFT to preprocess speech signals as … Read more
Neural Network Models It’s that time of the week again! Today, Xiao Jun is sharing neural network models for everyone to learn together! Neural networks are complex network systems formed by a large number of simple processing units (called neurons) that are widely interconnected. They reflect many of the basic features of brain function and … Read more
Source: PaperWeekly This article is about 4600 words long, and it is recommended to read it in 10 minutes. This article analyzes the reversible residual networks as the basis. Why Use Reversible Networks? Because both encoding and decoding use the same parameters, the model is lightweight. The reversible denoising network InvDN has only 4.2% of … Read more