1DCNN

Can Vision Transformers Surpass CNNs in Image Recognition?

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Can Vision Transformers Surpass CNNs in Image Recognition?

Machine Heart reports Machine Heart Editorial Department In the field of computer vision, Convolutional Neural Networks (CNNs) have always been dominant. However, researchers are continuously attempting to apply Transformers from the NLP domain to cross-disciplinary studies, with some achieving quite impressive results. Recently, an anonymous ICLR 2021 submission paper directly applied the standard Transformer to … Read more

Mastering Classic Models for Sentiment Analysis: CNN, GRNN, CLSTM, TD-LSTM/TC-LSTM

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Mastering Classic Models for Sentiment Analysis: CNN, GRNN, CLSTM, TD-LSTM/TC-LSTM

Machine Heart Column This column is produced by the Machine Heart SOTA! Model Resource Station, updated weekly on the Machine Heart public account every Sunday. This column will review common tasks in the fields of natural language processing and computer vision, and detail the classic models that have achieved SOTA on these tasks. You can … Read more

Simple Explanation of Neural Networks

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Simple Explanation of Neural Networks

This article is a note from Andrew Ng’s DeepLearning.ai course, covering the content of neural networks. The previous part can be found in[Simple Explanation of Neural Networks Part One] 4Activation Function When building a neural network, one important question to consider is which activation function to use for each independent layer. In logistic regression, the … Read more

Explaining The Development of Explainable AI and Deep Learning

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Explaining The Development of Explainable AI and Deep Learning

Click the “Expert Knowledge” above to follow for more AI insights! Source: Zhihu – Qs.Zhang https://zhuanlan.zhihu.com/p/30074544 【Introduction】Hello everyone, my name is Zhang Quanshi, a postdoctoral researcher at UCLA. Currently, I lead a team in Professor Zhu Songchun’s lab, focusing on explainable AI. The title of this article is quite grand; in this short essay, I … Read more

Understanding Deep Learning: From Neurons to BERT

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Understanding Deep Learning: From Neurons to BERT

Ali Sister’s Guide: BERT, a landmark in the field of natural language processing, did not appear out of nowhere; it has its development principles behind it. Today, the Ant Financial Wealth Dialogue Algorithm Team has organized and compared the development history of deep learning models in the field of natural language processing. From simple neurons … Read more

Innovative Network Structures of Convolutional Neural Networks

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Innovative Network Structures of Convolutional Neural Networks

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

Understanding Convolutional Neural Networks (CNN)

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Understanding Convolutional Neural Networks (CNN)

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

Understanding the Mathematical Essence of Convolutional Networks

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Understanding the Mathematical Essence of Convolutional Networks

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

Research on Electromagnetic Signal Recognition Based on CNN-Transformer Fusion Model

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Research on Electromagnetic Signal Recognition Based on CNN-Transformer Fusion Model

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