[Image] Convolutional Neural Networks (CNN), one of the classic forms of deep learning neural networks, is named for its computation process that includes convolution operations. CNNs extract local features from image data using convolutional layers, followed by pooling layers (Pooling Lay…
Follow the official account “ML_NLP“ Set as “Starred“, heavy content delivered first time! As a major part of deep learning, model architecture has always been a hot topic of research. Besides AutoML technology, what are some unconventional and innovative network architectures? 1 Author: Yan You San Source: https://www.zhihu.com/question/337470480/answer/766380855This article has been authorized for reprint by … Read more
Brothers, today we are going to talk about a particularly “high-end” but actually very practical and interesting technology – Convolutional Neural Networks (CNN). Don’t be afraid, the name sounds quite intimidating, but actually, if we chat in plain language, you will find that, hey, this thing is not that difficult! First, we need to understand … Read more
Recently, the research team proposed a method for assessing the severity of VR cybersickness using electroencephalogram (EEG) signals, published in “Displays”. This study, titled “Exploring quantitative assessment of cybersickness in virtual reality using EEG signals and a CNN-ECA-LSTM network”, induces various degrees of cybersickness through visual stimulation paradigms and collects corresponding EEG data. It extracts … Read more
Author: Zhang Xu Editor: Wang Shuwei This article has 4794 words and 27 images, reading time is about 11 minutes Forget it Read as long as you want Zero Reference Directory: 1. Convolutional Layer 1.1 The Role of Convolutional Layer in CNN 1.2 How Convolutional Layers Work 1.3 Convolutional Layers in AlexNet 2. Pooling and … Read more
Abstract: With the rapid development of communication technology today, the electromagnetic space environment has become increasingly complex, and the types of signals in the electromagnetic space have also diversified. Faced with various interferences in the electromagnetic space, accurately and effectively distinguishing the types of electromagnetic signals has become more challenging. To address this issue, a … Read more
Recently, researchers from Nanyang Technological University published a paper that describes the mathematical principles of convolutional networks. This paper explains the operations and propagation processes of convolutional networks from a mathematical perspective. It is very helpful for understanding the mathematical essence of convolutional networks and aids readers in implementing convolutional networks “from scratch” (without using … Read more
A beginner in CV, I write this article to help other novices like me understand how to easily learn and allow experts to reinforce their basics (manual dog head), feel free to leave any questions in the comment section for discussion~ 1. Overview Paper: Densely Connected Convolutional NetworksPaper link: https://arxiv.org/pdf/1608.06993.pdf As the Best Paper at … Read more
Applicable Platform: Matlab 2023 and above This program references the ChineseEIJournal“Power Grid Technology” online publication, literature: “Classification Method of Power Quality Disturbances Based on Markov Transition Field and Multi-Head Attention Mechanism“. The program is well-commented and full of valuable content. Below is a brief introduction to the article and the program! Innovations in the Literature:The … Read more
↑↑↑ Follow after Star ”Alchemy Notes Alchemy Notes Author: Jie Shao, Guest of Alchemy Notes 1DCNN Introduction Recently, many data competitions on Kaggle have featured the 1DCNN model. After reviewing related competitions, I found the concept of 1DCNN to be quite interesting. The basic idea is: First, we map the original features to a high-dimensional … Read more