This article uses a visual presentation to help you deeply understand the structure of the LSTM model. Recently, I have been learning about the application of LSTM in time series prediction, but I encountered a significant problem: after adding time steps to the traditional BP network, its structure becomes difficult to understand.At the same time, … Read more
Source: Deep Learning Enthusiasts This article is about 3300 words, and it is recommended to read for more than 10 minutes. This article uses a visual presentation to help you deeply understand the structure of LSTM models. I have recently been learning about the application of LSTM in time series prediction, but I encountered a … Read more
MLNLP(Machine Learning Algorithms and Natural Language Processing) is one of the largest natural language processing communities in China and abroad, gathering over 500,000 subscribers, covering domestic and international NLP master’s and doctoral students, university teachers, and corporate researchers.The vision of the community is to promote communication and progress between the academic and industrial sectors of … Read more
Editor’s Note This review categorizes recent innovations in CNN architectures into seven different categories based on spatial utilization, depth, multi-path, width, feature map utilization, channel enhancement, and attention. Deep Convolutional Neural Networks (CNN) are a special type of neural network that have demonstrated state-of-the-art results on various competitive benchmarks. The high performance achieved by deep … Read more
Source: Machine Heart This article is approximately 2774 words long and is recommended to be read in 13 minutes. This article introduces a novel large kernel attention module proposed by researchers from Tsinghua University and Nankai University, and constructs a new neural network named VAN that outperforms SOTA visual transformers based on LKA. As a … Read more
Approximately 1600 words, recommended reading time 7 minutes. This article will deeply analyze the underlying reasons for the decline in CNN research popularity and the development direction of this classic architecture in the new era. In the field of deep learning, Convolutional Neural Networks (CNNs) were once synonymous with computer vision. Since AlexNet’s groundbreaking success … Read more
Table of Contents | 2024 Issue 3 Special Topic: 6G Integrated Sensing and Computing Discussion on the Application of Integrated Communication Sensing Computing in the Internet of Vehicles Immersive XR Practices and Prospects Based on 6G Integrated Sensing and Computing Key Technologies for Integrated Sensing and Computing in Stereoscopic Traffic Systems Exploration of 6G Integrated … 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
Article Title: Overview of Robustness Verification for Feedforward and Recurrent Neural Networks All Authors: Liu Ying, Yang Pengfei, Zhang Lijun, Wu Zhilin, Feng Yuan First Affiliation: National Key Laboratory of Computer Science (Institute of Software, Chinese Academy of Sciences) Publication Date: 2023, 34(7): 3134-3166 Abstract With the advent of the intelligent era, intelligent systems deployed … Read more
Source: Machine Learning Algorithms This article is about 2400 words long and is suggested to be read in 5 minutes. This article illustrates the Self-Attention mechanism. 1. Difference Between Attention Mechanism and Self-Attention Mechanism The difference between Attention mechanism and Self-Attention mechanism: The traditional Attention mechanism occurs between the elements of the Target and all … Read more