Click on the above“Beginner’s Visual Learning“, select to add “Starred” or “Pinned“ Important content delivered at the first time This article is reprinted from: Computer Vision Alliance The most classic computer vision problem is 3-D reconstruction. It can basically be divided into two paths: one is multi-view reconstruction, and the other is motion reconstruction. The … Read more
Click the "Xiaobai Learns Vision" above, select to add "Star" or "Top" Heavyweight content delivered first time Author | Tomer AmitTranslator | Wan Yue, Editor | Tu MinProduced by | CSDN (ID: CSDNnews) The following is the translation: In this article, I will share 25 questions about deep learning, hoping to help you prepare for … Read more
This year, LSTM is trending! The original authors of LSTM have proposed xLSTM and Vision-LSTM, addressing previous limitations. At the same time, LSTM+Transformer has made it to Nature; various hybrid model architectures such as LSTM+CNN, LSTM+Attention are continuously refreshing SOTA. LSTM is definitely a great direction for generating ideas and publishing papers recently. I have … Read more
Selected from arXiv Author: Zhonghui You et al. Translated by Machine Heart Contributors: Siyuan, Yiming Using the basic idea of LSTM’s gating mechanism for pruning? Let the model decide which convolution kernels can be discarded. Remember when we understood LSTM, we found that it uses a gating mechanism to remember important information and forget unimportant … Read more
1. Introduction to CNN CNN is a type of neural network that utilizes convolutional calculations. It can reduce the original image with very large pixel sizes to a smaller pixel image while retaining the main features. This article elaborates on the content from Professor Li Hongyi’s PPT. 1.1 Why CNN for Images ① Why Introduce … Read more
If you don’t click the blue text to follow, the opportunity will fly away! CNN and RNN are the two most commonly used deep learning network architectures in deep learning. Some students may not be very clear about the differences between these two networks, and today I happened to see an image that can clearly … Read more
Deep learning is an important branch of artificial intelligence that has made significant progress in recent years. Among them, RNN, CNN, Transformer, BERT, and GPT are five commonly used deep learning models that have achieved important breakthroughs in fields such as computer vision and natural language processing. This article will briefly introduce these five models … Read more
This article shares an analysis of the mathematical principles behind CNNs, which will help you deepen your understanding of how neural networks work in CNNs. As a suggestion, this article will include quite complex mathematical equations. If you’re not accustomed to linear algebra and calculus, that’s fine; the goal is not to memorize these formulas … Read more
This article is reprinted from: Deep Learning EnthusiastsLink:https://www.zhihu.com/question/448924025/answer/1801015343Editor: Deep Learning and Computer VisionStatement: For academic sharing only, please delete if infringing Is CNN a Type of Local Self-Attention?Author: Hohuohttps://www.zhihu.com/question/448924025/answer/1791134786(This answer refers to: Li Hongyi’s 2021 Machine Learning Course)CNN is not a type of local attention, so let’s clarify what CNN and attention are doing. 1: … Read more
Hello everyone, I am Hua Ge. This article systematically and comprehensively organizes the introduction and algorithm principles of various deep learning models. At the beginning of the article, let me first introduce our company’s popular business. If you have any needs or ideas, feel free to chat! 1 Main Text Deep learning methods utilize neural … Read more