This article will cover the essence of ResNetthe principles of ResNetand the applications of ResNet to help you understand Residual Neural Networks (ResNet). Residual Neural Network ResNet 1. The essence of ResNetResNet’s definition: Residual Neural Network (ResNet) is an architecture of deep convolutional neural networks (CNN) that addresses the degradation problem in training deep networks … Read more
Computer deep learning systems based on artificial neural network algorithms have become a cutting-edge focus in the field of computer research. The principle is to enable artificial neural network algorithms to learn like the human brain through practice. In addition to being used for facial and voice recognition, it can also search through vast amounts … Read more
This article will coverthe essence of fine-tuningthe principles of fine-tuning, and the applications of fine-tuning in three aspects to help you understand model fine-tuning Fine-tuning . Fine-tuning Model Fine-tuning The Essence of Fine-tuning How to Utilize Pre-trained Models?Two popular methods are Transfer Learning and Fine-tuning. Transfer Learning is a broader concept that includes various methods … Read more
This article will cover the essence of U-Net principles of U-Net and its applications in three aspects to help you understand the image segmentation network | U-Net. U-Net 1. U-Net essence Definition of U-Net:A convolutional neural network based on deep learning, mainly used for image segmentation tasks, especially the segmentation of biomedical images.It consists of … Read more
This article will explain the essence of pre-training principles, and applications in three aspects, helping you understand model pre-training Pre-training. Pre-training 1.Essence of Pre-training AI = Data + Algorithms + Computing Power Three Elements of AI Dataset:Data is one of the three pillars of AI and is very important in AI technology. Datasets are generally … Read more
This article will cover the essence of GNN、GNNprinciples、GNNapplications in three aspects, allowing you to understand Graph Neural Networks (GNN) in one article. Graph Neural Network (GNN) 1. The Essence of GNNEssence of GNN The definition of GNN:GNN, or Graph Neural Network, is a deep learning model based on graph structures, specifically designed to handle graph … Read more
This article will coverbiological neural networks, artificial neural networksandneural network trainingand classification and applications in four aspects, bringing you to understand artificial neural network ANN in one article. 1.Biological Neural Networks Basic Definition: Baidu Encyclopedia:Biological Neural Networks generally refer to the networks composed of neurons, cells, synapses, etc. in biological brains, used to generate consciousness … Read more
This article will cover three aspects of the essence of Transformer, the principles of Transformer, and the applications of Transformer, helping you understand Transformer (overall architecture & three types of attention layers) in one article. Transformer 1. Essence of Transformer The origin of Transformer:The Google Brain translation team proposed a novel simple network architecture called … Read more
Source: CodeMeals cnblogs.com/fengfenggirl/p/bp_network.html Neural networks were once very popular, went through a period of decline, and are now gaining popularity again due to deep learning. There are many types of neural networks: feedforward networks, backpropagation networks, recurrent neural networks, convolutional neural networks, etc. This article introduces the basic backpropagation neural network (BP), focusing on the … Read more
Course Introduction In the “Opinions on Promoting New Urban Infrastructure Construction to Create Resilient Cities” issued by the Ministry of Housing and Urban-Rural Development in 2024, it mentions intelligent municipal services, smart cities, smart residential areas, digital homes, CIM, etc. Future urban construction cannot be separated from “intelligence”. This course will focus on artificial intelligence … Read more