Introduction In this article, I will explore a common practice in representation learning—using the frozen states of pre-trained neural networks as feature extractors. Specifically, I am interested in comparing the performance of simple models trained using these extracted neural network features with that of fine-tuned neural networks initialized with transfer learning. The intended audience is … Read more
Author | Howard Source | Zhihu 1. NLP’s Head Start The history of NLP development is quite early, as the need for language processing has existed since the invention of computers. Various string algorithms have been intertwined with the history of computer development. The great Chomsky proposed generative grammar, which is the most basic framework … 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
Introduction “Plugins” are enhancements that can be easily integrated into existing systems, truly embodying the plug-and-play concept. The “plugins” discussed in this article can enhance the CNN’s ability to handle transformations like translation, rotation, and scale, as well as multi-scale feature extraction, and can be found in many SOTA networks. Pytorch training camp, master coding … Read more
↑ ClickBlue Text Follow the Extreme City Platform Author丨Peter Pan Editor丨Extreme City Platform Extreme City Guide So-called “plug-ins” should enhance the performance while being easy to integrate, truly achieving plug-and-play functionality. The “plug-ins” discussed in this article can enhance the CNN’s capabilities in translation, rotation, scaling, and multi-scale feature extraction, making their presence felt in … Read more
Convolutional Neural Networks (CNN) are a type of feedforward neural network that includes convolutional computations and has a deep structure. They are one of the representative algorithms of deep learning. This article aims to introduce the basic concepts and structures of CNN, as well as the fundamental ideas behind CNN architecture design. This article is … Read more
01 Introduction This article reviews some of the more ingeniously designed and practical “plugins” used in CNN networks. The so-called “plugins” are modules that do not alter the main structure of the network and can be easily integrated into mainstream networks to enhance their feature extraction capabilities, achieving a plug-and-play functionality. Many similar reviews claim … Read more