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
This article first summarizes the development history of large model technology, the iterative path of autonomous driving models, and the role of large models in the autonomous driving industry. Next, it details the basic definition, fundamental functions, and key technologies of large models, especially the Transformer attention mechanism and the pre-training-fine-tuning paradigm. The article also … Read more
CNN and RNN are the two most commonly used deep learning network structures in deep learning, and some students may still be unclear about the differences between these two networks. Now let’s illustrate the specific applications of CNN and RNN with a diagram: One to One: This represents the scenario of the CNN network, from … Read more
In the field of deep learning, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Deep Neural Networks (DNN) are the three most widely researched and applied neural network models. They each have their own focus in terms of structure, function, and applicable scenarios, complementing each other. This article will provide a detailed analysis of … Read more
Artificial Intelligence Machine Learning Deep Learning Introduction For beginners, it can be difficult to distinguish between artificial intelligence (AI), machine learning (ML), and deep learning (DL) when first encountering them, as well as to understand their connections, concepts, and what they can do. 1 Concepts and Definitions In simple terms, artificial intelligence is about making … Read more
Popular Science Article The Past and Present of Machine Translation From the Tower of Babel to Esperanto, and now to machine translation, humanity has been trying to eliminate the barriers of language communication. The Tower of Babel fell short, Esperanto failed, where will machine translation go? Let us first review the development history of machine … Read more
Follow the official account “ML_NLP“ Set as “Starred“, receive heavy content promptly! Selected by | Ahmed BESBES Author | Ahmed Besbes Transferred from | Machine Heart This article introduces 7 models for text classification tasks, including traditional bag-of-words models, recurrent neural networks, convolutional neural networks commonly used in computer vision tasks, and RNN + CNN. … Read more
Click on the above“Beginner Learning Vision” to select Star or “Pin” Important content delivered immediately This issue we will introduce how to use OpenCV and TensorFlow to implement squat detection. During the quarantine period, our physical activities are very limited, which is not good. When doing some home exercises, we must always maintain a high … Read more